Networking system of interconnected devices for emissions data collection in an agricultural environment

Abstract

An internet-of-things communications network deployed within an environment is disclosed. The system may be used to analyze emissions related data within an agricultural environment and provide a calculation regarding a monitored environment's carbon emissions. The system has a communications network allowing for the transmission and reception of information. The network may include a plurality of devices capable of obtaining information related to agricultural actions, an access point, and a remote database. The communications networks may deploy a modified Wi-Fi HaLow communications protocol. Further, a data analysis module may be implemented to analyze and report information related to the monitored environment. The data analysis module may be utilized in partitions to optimize processing of the system where some execution of the data analysis module may occur at the access point and other execution occurs at the remote database.

Description

PCT Patent Application Attorney Docket Number: 47004-244178 NETWORKING SYSTEM OF INTERCONNECTED DEVICES FOR EMISSIONS DATA COLLECTION IN AN AGRICULTURAL ENVIRONMENT CROSS-REFERENCE AND PRIORITY CLAIM TO RELATED PATENT APPLICATIONS

[0001] This international PCT patent application claims priority to U.S. Provisional patent application serial number 63 / 572,818, filed April 1, 2024, and titled “Networking System of Interconnected Devices for Emissions Data Collection in an Agricultural Environment,” the entire disclosure of which is incorporated herein by reference. STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH AND DEVELOPMENT

[0002] N / A INTRODUCTION

[0003] The present disclosure relates generally to the field of network communications between devices to exchange data, and more specifically, to systems, architecture, and methods for an internet-of-things communications network deployed within an agricultural environment to receive and transmit data related to emissions.

[0004] The agricultural industry is currently undergoing a shift looking to adapt and incorporate electronic based technologies and other industrial developments into its field of endeavor. The latest stage of agricultural development looks to implement and leverage internet-of-things (IoT) technology, artificial intelligence (AI), big dataPCT Patent Application Attorney Docket Number: 47004-244178 analytics, improved robotic applications, and precision agriculture calculation into the field. These technological advancements look to address challenges such as global food production, resource sustainability, and climate change adaptation. However, promoting sustainable farming practices presents a formidable challenge for the agricultural industry. The U.S. Department of Agriculture determined that the agricultural sector alone contributes over 10% of all U.S. greenhouse gas emissions. The agricultural sector’s contribution is predicted to surge to 32% by 2050 if current agricultural trends persist.

[0005] Traditional methods of monitoring agricultural emissions, such as carbon- based emissions, are encumbered by numerous challenges. To start, existing sensing devices and sensors suffer from inconsistent connectivity and data exchange capabilities. Using these inadequate sensors can create and lead to data monitoring gaps due to limited coverage and non-uniform standards. Additionally, there does not exist a complete, comprehensive system to employ for monitoring in current agricultural environments. The absence of a comprehensive end-to-end interconnective architecture of local devices impedes the efficient assessment and management of potential carbon footprints. Further, modern farming techniques have increased both size and number of resources used to run a large-scale agricultural operation. Within these larger scale environments, optimizing resource utilization, including reducing fuel and energy consumption, necessitates precise tracking of agricultural machinery and vehicles. These challenges underscore the need for an innovative and integrated approach to address agricultural emissions and carbon footprint monitoring.PCT Patent Application Attorney Docket Number: 47004-244178

[0006] The inventors of the present disclosure recognize the challenges facing the current agricultural ecosystem and how current agricultural inefficiencies and techniques aid in creating this substantial quantity of greenhouse gas emissions. The inventors seek to address this issue head on with the systems, architecture, and methods disclosed within this disclosure. The work, discoveries, and concepts set forth by the inventors to address these agricultural emissions concerns are disclosed herein, and in one example, as the form of an improved networking system of interconnected devices for emission data collection within an agricultural environment. The following disclosure of the associated systems, architecture, and methods of the inventors’ advancements may take the form of an Internet of Carbon Things (IoCT) solution. This example Internet of Carbon Things (IoCT) solution can be employed with current and future agricultural practice for sustainable carbon monitoring within these agricultural systems. This example solution works to pioneer and integrate improved wireless technology, such as but not limited to communication technology that may be employed within a Wi-Fi HaLow communication structure, to assist with collecting, monitoring, and accounting for emissions related emission data / information associated with a bounded agriculture environment. Using improved wireless communication technology and network architecture in such a manner presents current agricultural practice with an efficient, long-range, and low-power wireless communication standard that may be used to catalyze a paradigm shift in carbon footprint monitoring and help achieve sustainable farming practices.PCT Patent Application Attorney Docket Number: 47004-244178

[0007] Further features and advantages of the disclosed embodiments, as well as the structure and operation of various elements of the disclosed embodiments, are described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The accompanying drawings, which are incorporated in and form a part of the specification, illustrate the disclosed embodiments and, together with the description, explain certain inventive principles. In the drawings:

[0009] Figure 1 illustrates an example of an internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0010] Figure 2 illustrates an example access point that may be an edge computing system with networking capabilities within the internet-of-things communications network deployed within an agricultural environment in an embodiment of the disclosure.

[0011] Figure 3 illustrates an example sensor, GPS unit, or station of a plurality of devices that may be located on a network communications system associated with an internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0012] Figure 4 illustrates an example relay of a plurality of devices that may be located on a network communications system associated with an internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.PCT Patent Application Attorney Docket Number: 47004-244178

[0013] Figure 5 illustrates an example positioning of relays and sensors with access points that may be located on a network communications system associated with an internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0014] Figure 6 illustrates an example of an angular separation-based relay placement strategy that may be employed with a plurality of devices that may be located on a network communications system associated with the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0015] Figure 7 illustrates an example proposed protocol stack for a modified Wi-Fi HaLow communications protocol that may be used by the devices and components of the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0016] Figure 8 illustrates an example of possible slot allocations within the modified Wi-Fi HaLow communications protocol network that may be used by the devices and components of the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0017] Figure 9 illustrates an example of possible traffic load-based dynamic grouping for avoiding congestion with a plurality of devices that may be located on a network communications system associated with the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.PCT Patent Application Attorney Docket Number: 47004-244178

[0018] Figure 10 illustrates an example of the data flow within the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0019] Figure 11 illustrates an example of subprocesses and routines that may be present within the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0020] Figure 12 illustrates an example of a preprocessing algorithm of executable code that can be implemented at the edge computing system of the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0021] Figure 13 illustrates an example of a tier-1 carbon footprint calculation algorithm of executable code that can be implemented at the edge computing system of the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0022] Figure 14 illustrates an example of a tier-2 carbon footprint calculation algorithm of executable code that can be implemented at the edge computing system of the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0023] Figure 15 illustrates an example of a tier-3 carbon footprint calculation algorithm of executable code that can be implemented at the edge computing system of the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0024] Figure 16 illustrates an example of a possible dataset development process that can be executed by software applications within the cloud network associatedPCT Patent Application Attorney Docket Number: 47004-244178 with the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0025] Figure 17 illustrates an example of a possible artificial intelligence or machine learning (AI / ML) training process that can be executed by software applications within the cloud network associated with the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0026] Figure 18 illustrates an example of a possible generation process to determine and output useful or requested analysis via the trained artificial intelligence or machine learning (AI / ML) model that may be employed with the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0027] Figure 19 illustrates an example of a possible delivery process related to the training of artificial intelligence or machine learning (AI / ML) models and a subsequent deployment to edge computing systems of implementation of a potential action locally within the monitored environment associated with the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0028] Figure 20 illustrates an example graphical user interface screenshot viewable on a display of the edge computing system by users of the internet-of- things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0029] Figure 21 illustrates a second example graphical user interface screenshot viewable on a display of the edge computing system by users of the internet-of-PCT Patent Application Attorney Docket Number: 47004-244178 things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0030] Figure 22 illustrates an example graphical user interface screenshot viewable on a dashboard display of the remote databases in the cloud network accessible by users of the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0031] Figure 23 illustrates the resulting throughput measurements across Modulation and Coding Scheme (MCS) indices recorded using the example technology to create the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure.

[0032] Figure 24 illustrates a charting of channel 1^MHz and the added overhead of RTS / CTS of round-trip times compared to 2^MHz with Data + ACK alone recorded using the example technology to create the internet-of-things communications system deployed within an agricultural environment in accordance with an embodiment of the disclosure. DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

[0033] The foregoing and other features and advantages of the invention will become more apparent from the following detailed description of exemplary embodiments, read in conjunction with the accompanying drawings. Before turning to the figures, which illustrate certain example embodiments in detail, it should be understood that the present disclosure is not limited to the details or methodology set forth in the description or illustrated in the figures. It should also be understood that the terminology used herein is for the purpose of description only and should not bePCT Patent Application Attorney Docket Number: 47004-244178 regarded as limiting. The detailed description and drawings are merely illustrative of the present disclosure rather than limiting, the scope of the invention being defined by the appended claims and equivalents thereof.

[0034] Referring generally to the figures, described herein are systems, architecture, and methods for an internet-of-things communications system. The internet-of-things communications system may operate as a network deployed within an agricultural environment to receive and transmit data. In one example, this data may relate to emissions. The systems, architecture, and methods disclosed herein may be used for purposes of monitoring any type of select agricultural information or data within the monitored agricultural environment. One example of select agricultural information or data may relate to carbon-based emissions, but the internet-of-things communications system is not limited only to emission-based monitoring purposes. The present disclosure of this discovery offers a scalable, accessible, and accurate solution to an urgent problem of reducing agricultural carbon emissions. By revolutionizing carbon footprint monitoring, as well as the communications network and systems upon which it operates, the disclosed internet- of-things communications network deployed within an agricultural environment may be both precise and actionable. Further, the disclosed internet-of-things communications network deployed within an agricultural environment looks to empower the agricultural sector to optimize resource allocation, minimize environmental impact, and advance sustainable practices. The disclosed improvements in wireless technology, such as but not limited to that which may be employed within a Wi-Fi HaLow communication structure, are designed to be useable within the agricultural internet-of-things communications system andPCT Patent Application Attorney Docket Number: 47004-244178 possess the potential to transform agriculture, contributing significantly to global climate change mitigation and fostering a sustainable future.

[0035] The current state of agricultural communication and data collection systems presents numerous shortcomings to the future needs of those within the agricultural fields and are extremely limited with both the physical and computational solutions they can provide those operating in an agricultural environment. The current state of agricultural communication and data collection systems primarily include independent systems. These systems may include sensor-based monitoring systems for environmental and crop health metrics, precision agriculture technologies like global positioning systems (GPS) and drones for farming efficiency, or general agricultural communication and data collection solutions for extremely high-level farm management. While these systems may improve specific and targeted aspects of individual farming operations, these systems lack implementation as a comprehensive aggregation of these different individual abilities within a commonly deployable system. Further, these current individual systems lack a focus on carbon emission tracking and management. Current greenhouse gas emission estimation models within an agricultural environment rely on generalized data and nothing more. These current systems do not provide real-time, location-specific analysis. Additionally, most agricultural data analytics platforms perform targeted processing allocation and resources towards high-level crop productivity and disease detection and are not capable of extending their scope to detailed carbon emission monitoring. This landscape underscores the distinctiveness and need felt for the disclosed agricultural internet-of-things communications system.PCT Patent Application Attorney Docket Number: 47004-244178

[0036] Existing solutions in the agricultural sector present several drawbacks and limitations. Such failing can particularly be viewed within the context of comprehensive carbon emission tracking, management, systems, and system architecture. The known failings of current agricultural communication and data collection systems are numerous. For example, current agricultural communication and data collection systems offer limited to no focus on carbon emissions. Such current systems are employed to primarily monitor general environmental conditions, crop health, and farming efficiency. Thus, these current offerings lack any specific functionality to track and analyze carbon emissions with precision and detail which is a critical aspect of consideration when deploying sustainable farming practices.

[0037] Further, current agricultural communication and data collection systems with any potential emission related data capabilities exhibit nothing more than a limited output of generalized greenhouse gas (GHG) estimations. Current greenhouse gas (GHG) emission estimation models offered, but not necessarily employed within an agricultural environment, often nothing more than use of generalized data and assumptions. These models do not offer any potential real-time, location-specific analysis that is needed and necessary for accurate carbon footprint assessment in diverse agricultural settings.

[0038] Moreover, current agricultural communication and data collection systems suffer from significant connectivity and Range Issues: Many existing IoT systems in agriculture face challenges with connectivity and range, particularly in remote or extensive farming areas. This limitation hampers the ability to collect comprehensive data across large agricultural landscapes.PCT Patent Application Attorney Docket Number: 47004-244178

[0039] As another example, current agricultural communication and data collection systems possess limited data integration and processing capabilities. Current system offerings lack any type of efficient data integration and processing thereof when such received data for processing originates from various sources or as various data formats. This limitation results in a fragmented understanding of a farm or an agricultural environment and its overall environmental impact, and hinders the development of targeted strategies to address, correct, or alter agricultural processes for potential emission reduction.

[0040] Current agricultural communication and data collection systems also lack scalability and customization. These current solutions do not scale effectively to accommodate the diverse and evolving needs of modern agriculture. This is especially true as modern agriculture looks to implement further innovative technology within its operations. The current system offerings lack the needed level of customization to address specific emission issues, including but not limited to, geographically specific carbon footprint tracking and the management requirements of different farms within diverse geographical locations.

[0041] Further current offerings of agricultural communication and data collection systems suffer from severe technological limitations. These current solutions do not, and cannot, fully leverage advanced technologies such as long-range, low-power communication networks, and sophisticated data analytics. Both of which are crucial for effective emission monitoring and management especially for carbon related emissions.

[0042] Finally, current agricultural communication and data collection systems lack defined user accessibility and decision supportive functionality. These currentPCT Patent Application Attorney Docket Number: 47004-244178 systems do not provide user-friendly interfaces or actionable insights based on any collected data or processed calculations thereof. Existing systems are thus limited in their practical utility for farmers and field managers when making informed decisions for sustainable practices can affect the overall profitability and economic sustainability of the agricultural location.

[0043] The multiple technical solutions that can be found within the systems, architecture, and methods disclosed within the present application improve and address the above challenges and shortcoming currently present with existing agricultural communication and data collection systems. More specifically, the advancements disclosed herein address and overcome these shortcomings with a fresh approach and design towards network communication, data collection, monitoring, and predictive analysis for agricultural environments and emissions data. The present disclosure introduces a system, architecture, and method-based solution to these failings. The disclosed internet-of-things communications network deployed within an agricultural environment may be implemented with a novel networking communication architectural structure. This network communication structure disclosed may, in some embodiments, employ use of Wi-Fi HaLow technology to facilitate long-range data collection. The network communication structure working within the disclosed internet-of-things communications network deployed within an agricultural environment looks to also integrate edge computing and artificial intelligence for real-time emissions calculations that may focus on the carbon footprint of the monitored location. The disclosed internet-of-things communications network deployed within an agricultural environment thus can lead to sustainable farming recommendations in agricultural systems. Thus, the disclosedPCT Patent Application Attorney Docket Number: 47004-244178 internet-of-things communications network deployed within an agricultural environment addresses these above challenges and more by providing a scalable and comprehensive framework for emissions monitoring, data analysis, and promoting environmentally conscious farming practices.

[0044] Additional benefits of the technical solutions disclosed herein include, but are not limited to, at least the following examples. A first example technical solution presented with the disclosed internet-of-things communications network deployed within an agricultural environment includes significant advancements with targeted carbon emission tracking. Unlike the existing high-level, general, sensor-based systems, the disclosed internet-of-things communications network deployed within an agricultural environment specifically focuses on tracking, calculating, and reporting carbon emissions to provide a more targeted approach to environmental sustainability in agriculture. This is accomplished, at least in part, by a dedicated focus of the disclosed solution on carbon emission tracking with specific sensors and algorithms. Utilization of these specific sensors and algorithms provide the disclosed solution with the ability to ascertain and report Real-time, location-specific carbon footprint analysis tailored to a diverse subset of monitored agricultural environments.

[0045] A second example technical solution presented with the disclosed internet- of-things communications network deployed within an agricultural environment includes novel advances upon the communication network architecture itself. These improved network architecture advancements are performed to optimize data collection, pathing, and data transmission within the deployed agricultural environment. Further, these improved network architecture advancements are part of the overall disclosed solution. They are presented to address current challengesPCT Patent Application Attorney Docket Number: 47004-244178 facing most agricultural locations and their associated limitations regarding data collection and transmission, including but not limited to range, reliability, and power efficiency that prevent the feasible implementation / operation of any internet-of-things type communications networks. Overall, the improved network architecture advancements boost connectivity and data transmission capabilities using a novel application of wireless communication technology, being Wi-Fi HaLow technology in some embodiment, to overcome existing range and power issues.

[0046] A third example technical solution presented with the disclosed internet-of- things communications network deployed within an agricultural environment includes a fully encompassing approach to collect and process emissions, potentially carbon based, data with analytical software. The disclosed analytical software as part of the agricultural internet-of-things communications network solution is designed to interpret, process, and report data specifically related to the monitored location and may further focus on comprehensive carbon emissions. The disclosed analytical software is a significant advancement over general data analytics platforms in that it provides users of the disclosed solution actionable insights specific to monitored agricultural location and its associated future, and potentially future, carbon footprint for optimal management. The advanced analytical capabilities of the disclosed analytical software may further leverage machine learning and artificial intelligence for predictive insights not currently possible. Moreover, the disclosed analytical software provides a user-friendly interface designed for ease of use and effective decision-making when it is employed to support sustainable farming implementations and techniques.PCT Patent Application Attorney Docket Number: 47004-244178

[0047] A fourth example technical solution presented with the disclosed internet-of- things communications network deployed within an agricultural environment includes improvements with integration and interdependency of its disclosed subsystems. The interdependent nature of the disclosed internet-of-things communications network being a separate, yet united solution employed between the network architecture and analytical software to create a cohesive system that is more effective than the sum of its parts. Together, additional uses, functionalities, and features are possible with the disclosed internet-of-things communications network system and software. This cohesive system presents as a scalable and customizable solution to suit various agricultural needs and practices. The unification of the features disclosed within the internet-of-things communications network deployed within an agricultural environment is not present or possible in the current fragmented internet-of-things solutions within the agriculture space.

[0048] Referring to the accompanying drawings, Figure 1 illustrates an example system 100 that may be deployed within an environment 105 or location performing agricultural operations. The system may be a communications system and network interconnecting and allowing for communication between multiple devices or nodes in an internet-of-things type configuration. The system 100 may be designed to establish a robust framework for sustainable agricultural practices for the environment into which it is placed. The system 100 may include a plurality of subsystem components that operate cohesively to create the disclosed system 100. For example, one potential subsystem of the system 100 may be a network communications system 110. Within the network communications system 110, a plurality of devices 115 may be interconnected to one another to create thePCT Patent Application Attorney Docket Number: 47004-244178 architectural framework of the network communications system 110. This interconnection of the plurality of devices 115 may form an internet-of-things communications network whereby data may be transmitted and received by the plurality of devices 115 connected to and part of the network communications system 110. The framework of the network communications system 110 may include the integration of the plurality of devices 115. This plurality of devices 115 may include, but are not limited to specialized sensors 118, nodes / stations 120, relays / relay nodes 125, edge computing systems / access points 130, vehicles / machinery 135, drones 140, tracking devices, individuals, and external computing systems all interconnected through a communications protocol connection. Each subset of the plurality of devices 115 may be collectively grouped as a common unit to communicate as directed by the network communications system 110 within the monitored environment 105. In example configurations of the system 100, each individual device of a particular subset of senor type may be configured to communicate with a select, predetermined node station 120, relay 125, or edge computing system / access point 130, or subset of node stations 120, relays 125, or edge computing systems / access points 130. This communication connection can by determined by the network communications system 110 in multiple manners, such as directing communications by an individual device to a specific node station(s) 120, relay(s) 125, or edge computing system(s) / access point(s) 130. In other configurations of the system 100, the communication connection can by determined by directing communications by an individual device to the closest node station(s) 120, relay(s) 125, or edge computing system(s) / access point(s) 130, or to a second individual device with communication capabilities that is closest toPCT Patent Application Attorney Docket Number: 47004-244178 geographical location of the individual device at the moment data is requested or transmitted by the network communications system 110.

[0049] In some example embodiments, communications by the network communications system 110 may be hardwired between some or all the plurality of devices 115 or their subset sensor groupings. In other example embodiments, communications by the network communications system 110 may be wireless between some or all the plurality of devices 115 or their subset sensor groupings. In some example configurations, it is envisioned that wireless communication connections between the plurality of devices 115 on the network communications system 110 may be accomplished by utilizing a wireless network protocol such as a Wi-Fi HaLow-based network communications protocol. Of course, other wireless network communications protocols may be employed, are possible, and can be used for communication purposes between the plurality of devices 115 on the network communications system 110.

[0050] Utilization of the Wi-Fi HaLow-based network communications protocol may include implemented engineering improvements to the present network communications system 110 viewed in Figure 1. These improvements will be discussed in further detail below and create an improved communication architecture not achievable with other commonly used wireless system communication protocols or by using the standard Wi-Fi HaLow network communications protocol. Use of the disclosed Wi-Fi HaLow-based network communications protocol within the network communications system 110 may be done to accomplish the overall system goals to maintain and create possible long-range communication pathways for the plurality of devices 115 associated with the network communications system 110. Thus, thePCT Patent Application Attorney Docket Number: 47004-244178 disclosed Wi-Fi HaLow-based network communications protocol deployed on the network communications system 110 may enable efficient data collection even in the remote areas of environment 105, such as a large farm or agricultural environment.

[0051] One of the plurality of devices 115 on the network communications system 110 may be a computing system 130. In some embodiments, the pathing of communication between the plurality of devices 115 may all lead to this computing system 130. The computing system 130 may be an edge type server computing system that is resident on an access point 130 of the network communications system 110. The edge computing system / access point 130 operating as the edge computing system main communication terminal for the network communications system 110 may be physically located within the geographical boundary of the agricultural environment 105 where the system 100 and the network communications system 110 is deployed for use. In other embodiments, the edge computing system / access point 130 may be remotely located away from the geographical boundary of the agricultural environment 105, and another device of the plurality of the devices 115 may communicate any required data or information to the edge computing system / access point 130 present at the remote location. The edge computing system / access point 130 may be present and available for on-site computing operations and data processing tasks. The edge computing system / access point 130 may further provide the capability to ensure low-latency decision-making at the local physical location within environment 105. In this manner, the edge computing system / access point 130 may offer farmers, managers, or workers of the agricultural environment 105 real-time data access directly in thePCT Patent Application Attorney Docket Number: 47004-244178 physical field when working in the environment 105. Moreover, the presence of the edge computing system / access point 130 physically located within the geographical boundary of the agricultural environment 105 can allow for the immediate, real-time calculation of emissions data analysis and carbon footprints by the system 100.

[0052] The edge computing system / access point 130 may further connect to and be in communication with a remote database. The remote database may be a server, or a plurality of remote databases or servers. In some embodiments, this plurality of remote databases or servers may form a cloud network 145 for communications with the edge computing system / access point 130 in environment 105 and the remote database. The cloud network 145 of remote databases may further receive data and information from the edge computing system / access point 130 that may be processed and analyzed by the cloud network 145 of remote databases. At times, the cloud network 145 of remote databases may transmit data back to the edge computing system / access point 130 for utilization by the system 100 and the network communications system 110. The data transmitted back to the edge computing system / access point 130 from the cloud network 145 of remote databases may include processed data received initially from the edge computing system / access point 130 or new data received by cloud network 145 from a third- party database, server, or computing system not associated with the remote database but may be of use to the edge computing system / access point 130 and its environment 105.

[0053] The disclosed system 100 may be configured as an internet-of-things communications network deployed within an agricultural environment 105. The system 100, and an elevated level, involves a combination of advanced hardwarePCT Patent Application Attorney Docket Number: 47004-244178 and software elements. These can be understood to generally be represented as two different subsystems of the system 100. The network communications system 110 can be understood to generally be the subsystem that represents most of the hardware advancements. The software system 148 for data and analytical processing can be understood to generally be the subsystem that represents most of the software advancements. In an example embodiment, the features, and advancements of the software system 148 of the overall system may be resident and location on one or more remote databases in communication with the edge computing system / access point 130 through the cloud network 145. Both the hardware and software advancements presented on each of these subsystems contribute to the overall effectiveness of system 100 as an internet-of-things communications network deployed within an agricultural environment 105. Further, the hardware and software advancements presented on each of these subsystems distinguish the disclosed system 100 of an internet-of-things communications network deployed within an agricultural environment 105 from existing solutions available today for use in current agricultural environments, and use of the system 100, as an internet-of-things communications network, presents users with new and novel features not before available for agricultural environmental use. Discussion will first address the hardware subsystem, and advancements thereof, that may be present within the network communications system 110 as part of the system 100 as an internet-of-things communications network deployed within an agricultural environment 105. Later, aspects that may be present within the software system 148, and advancements thereof, will be discussed as well as how they may be used within the software system 148 for data and analytical processingPCT Patent Application Attorney Docket Number: 47004-244178 as part of the system 100 as an internet-of-things communications network deployed within an agricultural environment 105.

[0054] Figure 1 illustrates the usefulness of the network communications system 110 employing a Wi-Fi HaLow communication network having important modifications. These modifications to the Wi-Fi HaLow communications protocol for communication by components of the network communications system 110 present a game-changing communication technology for agricultural environments 105. Implementation and use of the modified Wi-Fi HaLow communications protocol on the network communications system 110 can create a holistic framework for carbon footprint monitoring within environment 105. Further, not only does the use of the modified Wi-Fi HaLow communications protocol improve the overall network structure of the network communications system 110, but also the capabilities of the network communications system 110 in these agricultural environments 105. Use of the modified Wi-Fi HaLow communications protocol by the network communications system 110 or the system 100 allows for further advancement within the software system 148 and its developed data analytic modules / applications that can be used to focus analysis of signal information received via the network communications system 110.

[0055] As viewed in Figure 1, the overall software system 148 with a plurality of data analytics modules can be seen. These data analytics modules can be resident as architecture of the software system 148 subpart associated with system 100 of an internet-of-things communications network deployed within an agricultural environment 105. As an example, system 100 may collect information. The information received by the plurality of devices 115, or field devices, can include dataPCT Patent Application Attorney Docket Number: 47004-244178 that can be calculated at either the edge computing system / access point 130, the cloud network 145 of remote databases, or at both locations. In some envisioned use scenarios, data calculations performed at the edge computing system / access point 130 may result in usable outputs to be implemented by the plurality of data analytics modules of the software system 148 located remotely within the cloud network 145. As viewed in Figure 1, the edge computing system / access point 130 that may communicate with the cloud network 145 of remote databases can perform an initial calculation measurement. This may be done in the form of an initial carbon emissions calculation associated with the area or environment 105 monitored by the system 100 or generally the agricultural environment’s initial carbon footprint calculations. Further, the cloud network 145 of remote databases connected and in communication with the edge computing system / access point 130, can perform further processing tasks related to the plurality of data analytics modules and their functions that may form part of the software system 148. For example, one module of the remote plurality of data analytics modules could be an advanced analytics module 155. The advanced analytics module 155 may function to perform advanced computational analytics on the data / information received and obtained by the current monitored agricultural environment 105. Another possible remote module of the remote plurality of data analytics modules could be a calculations and predictions module 150. The calculations and predictions module 150 may function to perform detailed calculations and predictive algorithms involving the monitored agricultural environment 105. These detailed calculations and predictive algorithms may be based on historical, trending, or other types of datasets that may be relevant to understand the trajectory, heading, or predictive analytics of the monitoredPCT Patent Application Attorney Docket Number: 47004-244178 agricultural environment 105. Another possible remote module of the remote plurality of data analytics modules could be a recommendation module 152. More specifically, the recommendation module 152 may be associated with outputting and providing farming or agricultural type recommendations. Outputs developed by the calculations and predictions module 150 may be useful to and used by the recommendation module 152. The recommendation module 152 after analyzing the necessary input data can then output and provide recommendations to address any trends, predictions, or discovered issues needing immediate attention for the monitored agricultural environment 105 employing the system 100 as an internet-of- things communications network. Another possible remote module of the remote plurality of data analytics modules could be a visualization module 160. The visualization module 160 may output this information calculated or determined by the plurality of data analytics modules resident in the software system 148 in a user friendly and easy visualization format. While part of the software system 148, the visualization module 160 output may be viewable by multiple computing devices associated with the system 100. The output of the visualization module 160 may be accessible by end user devices connectable to the network communications system 110 or edge computing system / access point 130, the edge computing system / access point 130 itself, or with the remote databases of the cloud network 145. In this manner, the calculated dataset outputs of the plurality of data analytics modules can be shown to an end user via a graphical user interface that is practical, organized, and structured both to the needs of the end user and to the relevancy of outputted and calculated data the plurality of data analytics modules determines are most appropriate or relevant to report. These graphical user interfaces may bePCT Patent Application Attorney Docket Number: 47004-244178 customizable and different based on the end user, the end user needs, access permissions, data type, or based on whether the data is being obtained from either the edge computing system / access point 130 or the remote databases of the cloud network 145.

[0056] The system 100 as an internet-of-things communications network deployed within an agricultural environment 105 looks to integrate a diverse set of sensors and sensor types across a variety of agricultural equipment, uses, and / or actions. For example, the plurality of data analytics modules of the software system 148 may be capable of categorizing emissions into tiers depending on the monitored object or the information contained within the transmitted data for the system 100 deployed within an agricultural environment 105. As an example, a Tier-1 designation may monitor direct emissions, such as those from machinery 135. An example Tier-2 designation may track purchased energy emissions. An example Tier-3 designation may cover all other indirect emissions that can be calculated within the monitored environment 105. Further, mobile equipment, such as but not limited to tractors and drones 140, may be equipped with GPS trackers along with specialized sensors 118 to measure emissions at their sources. These measured emissions may include exhaust gases and power consumption of the monitored object. Comprehensive data obtained by this diverse set of sensors and sensor types can then be transmitted via the interconnected plurality of devices 115 within the monitored environment 105 via the modified Wi-Fi HaLow communications protocol to ensure efficient data collection.

[0057] Further advancements of the plurality of data analytics modules of the software system 148 include the ability to perform computations and calculations at a local point such as the edge computing system / access point 130. As an example,PCT Patent Application Attorney Docket Number: 47004-244178 the local resident edge computing system / access point 130 of the environment 105 may perform certain carbon footprint calculations. In some embodiments, the edge computing system / access point 130 located within the monitored environment 105 at the farm-level conducts real-time carbon footprint calculations using data from the diverse set of sensors, sensor types, and tracking devices. By leveraging Global Warming Potential (GWP) factors, the edge computing system / access point 130 may quantify emissions for each tier and convey the results both locally and to the cloud network 145 of remote databases for enhanced precision. This distributed processing functionality and separation of the component parts able to operate and assist the plurality of data analytics modules of the software system 148 contained within the system 100 helps to minimize power use, allows for optimized resource allocation, and improves processing turn around for the overall system 100.

[0058] Furthermore, within the cloud network 145 of remote databases, the plurality of data analytics modules of the software system 148 can include additional modules for other specific purposes other than those described above and may also implement modules capable of more power calculations and analysis. These additional modules may include artificial intelligence (AI) type modules for processing via the cloud’s capabilities that can result in direct recommendations or tasks to be implemented within the monitored environment 105 of the system 100. For example, these AI type output recommendations may take the form of sustainable farming recommendations and practices relevant for the managers and workers associated with the monitored agricultural environment 105. General emission monitoring or carbon-based monitoring is only a subset part of the entire system’s capability and potential when deployed as an internet-of-things communications network for anPCT Patent Application Attorney Docket Number: 47004-244178 agricultural environment 105. The plurality of data analytics modules of the software system 148 can gather, analyze, and output a wealth of data, such as but not limited to equipment mobility, engine specifications, and real-time activities. These additional analytics with the plurality of data analytics modules of the software system 148 can further include machine learning models for specific features or functions in the environment 105. The capabilities of the system 100 and outputs of the plurality of data analytics modules of the software system 148 may provide predictive carbon footprint estimates and the formulation of sustainable farming recommendations for these machine learning modules as well as recommendations to be implemented at the local monitored agricultural environment 105. Thes additional module outputs, and all outputs of the plurality of data analytics modules of the software system 148, can also be communicated via a user-friendly web interface to ensure that farmers and field managers can easily access these insights.

[0059] Turning now to Figures 2 through 10, components of the network communications system 110 as part of system 100 will be addressed and described in greater detail. As stated earlier, the network communications system 110 may include a computing system in the form of an edge computing system / access point 130. Figure 2 illustrates an example edge computing system / access point 130 with networking capabilities. The edge computing system / access point 130 may be an access point of the overall system 100 and part of the network communications system 110. The inclusion of an edge computing system / access point 130 provides multiple uses and advancements found use of the overall system 100 as an internet- of-things communications network deployed within an agricultural environment 105. For example, the edge computing system / access point 130 may possess the abilityPCT Patent Application Attorney Docket Number: 47004-244178 of localized data processing and analysis. Employing an edge computing system / access point 130 with this capability in the system 100 of an internet-of- things communications network deployed within an agricultural environment 105 allows for real-time processing capabilities local to the monitored agricultural environment 105. Further, this capability of the edge computing system / access point 130 reduces reliance on remote database requiring constant cloud network 145 connectivity and resulting in the enablement of faster decision-making, especially at the local monitored agricultural environment 105.

[0060] In the network communications system 110, the access point (AP) plays a useful role in network communication. The access point may be the edge computer system 130 itself, or alternatively be second access point of the network communications system 110. The edge computing system / access point 130 receives data from the network via a transceiver 210 that may operate by radio frequency, and, in some embodiments, operate on a modified Wi-Fi HaLow communication protocol. The edge computing system / access point 130 is adept at managing all incoming information from either the sensors associated with the plurality of devices 115, relays 125, or other edge computing systems or access points operating within the local network. The edge computing system / access point 130 may be equipped with storage capabilities 230 to temporarily hold fresh data for local processing at the edge computing system / access point 130. With this feature, and edge computing system / access point 130 enables computational processing operations and may perform select computing operations of the system 100 at the edge locational site. The edge computing system / access point 130 may also feature a cellular modem 235 for internet connectivity to further enable the edge computing system / accessPCT Patent Application Attorney Docket Number: 47004-244178 point 130 to upload received data to the cloud network 145 of remote databases and download updated models and information from the cloud network 145. Use of cellular networks by the edge computing system / access point 130 is particularly advantageous in remote agricultural environments 105 where traditional internet connectivity might be limited. Thus, the cellular network capability ensures continuous and reliable communication between the local network where the edge computing system / access point 130 is found and the cloud network 145 of remote databases.

[0061] The edge computing system / access point 130 can be employed physically within the agricultural environment 105 where the network communications system 110 is present. In alternative arrangements, the edge computing system / access point 130 may be remote from the agricultural environment 105. The edge computing system / access point 130 may be implemented as part of a local set of computer system operating as one or more servers. The edge computing system / access point 130 may contain a processor 220, a memory 225, and a network interface 215. The processor 220, memory 225, and network interface 215 can interconnect with each other in any of a variety of manners (e.g., via a bus, via a network, etc.) The edge computing system / access point 130 may also be connected to a power supply 200. The edge computing system / access point 130 may pull power from through a wired connection or the power supply 200 may be contained as part of the edge computing system / access point 130 as a battery type component.

[0062] The network interface 215 can provide an interface for the edge computing system / access point 130 to connect to a network. In some embodiment, the edgePCT Patent Application Attorney Docket Number: 47004-244178 computing system / access point 130 may connect to a first network representing a local area network such as the network communications system 110. The connection to the first network may be wired, wireless, or both. Also, the edge computing system / access point 130 may connect to a remote network such as the cloud network 145 via a wired or wireless connection. The edge computing system / access point 130 may connect to the first network that may be a wireless network utilizing modified Wi-Fi HaLow communications. The second network may be the cloud network 145 having one or more databases and servers available for communication and data transfer to and from the edge computing system / access point 130. The remote database of the cloud network 145 can take the form of any suitable computing system (such as a desktop computer, laptop computer, tablet computer, or smartphone) or larger computing system such as a server, database, or server / database network. The plurality of devices 115 that may be in communication with the edge computing system / access point 130 on the network communications system 110 can take the form various types of specialized sensors 118, nodes / stations 120, relays / relay nodes 125, edge computing systems / access points 130, vehicles / machinery 135, drones 140, tracking devices, individuals, devices, smart phones, laptop computers, tablet computers, desktop computers, or other computing systems or the like all interconnected through a local communications network.

[0063] The first and second networks can be any suitable communication network or combination of communication networks, such as the Internet or a mesh network, suitable to send communications to, and receive communications from various telecommunications type devices. Through the networks, the edge computingPCT Patent Application Attorney Docket Number: 47004-244178 system / access point 130 can communicate information regarding data captured or received from other computing devices or the plurality of devices 115 on the network communications system 110 to the cloud network 145 of remote databases so that the remote databases can perform further operations on specific datasets. Alternatively, the edge computing system / access point 130 can communicate information locally via the locally implemented communication protocol of the network communications system 110 to other computing devices or the plurality of devices 115. The edge computing system / access point 130 may locally transmit data captured or received by it from remote databases the cloud network 145, other computing devices, or from individual devices of the plurality of devices 115 located on the network communications system 110. This local communication provides the devices connected to the edge computing system / access point 130 with the ability to use necessary data withing the local network for further operations. The edge computing system / access point 130 can communicate with the networks in a variety of ways including, but not limited to, Bluetooth, a Wi-Fi network, a wired local area network (LAN), Zigbee. The network interface 215 of the edge computing system / access point 130 may take any suitable form for carrying out network interface functions, examples of which include an Ethernet interface, a serial bus interface (e.g., Firewire, USB 2.0, etc.), a chipset, antenna adapted to facilitate wireless communication, and / or any other interface that provides for wired and / or wireless communication. The network interface may also include multiple network interfaces for the different networks, such as a cellular modem 235, to which the edge computing system / access point 130 may connect and communicate. Other configurations are possible as well.PCT Patent Application Attorney Docket Number: 47004-244178

[0064] The different networks to which the edge computing system / access point 130 may connect may operate upon different communication protocols or employ different interfacing communication techniques. For example, the local geographical network including the plurality of devices 115 and the edge computing system / access point 130 may be a node type network communicating as a plurality of nodes. The nodes can be referred to and include the plurality of devices 115 and outside structures such as various types of specialized sensors 118, nodes / stations 120, relays / relay nodes 125, edge computing systems / access points 130, vehicles / machinery 135, drones 140, tracking devices, individuals, devices, smart phones, laptop computers, tablet computers, desktop computers, computing systems, cellular towers, radio towers, base stations, base transceiver stations, etc., and include equipment for wireless and cellular communication. For example, the nodes may include various antennae, transmitters, receivers, transceivers, digital signal processors, control electronics, global positioning receivers, and electrical power sources. The nodes may be configured such that each of the nodes can send and receive signals within a specified area (e.g., a cell). The area in which each of the nodes can send and receive signals can be determined by the implementation of the overall system 100 and may be shaped approximately like a hexagon. For example, a first node can send and receive signals (e.g., data) within a first area, a second node can send and receive signals within a second area, and a third node can send and receive signals within a third area. To send a signal from an originating location to a destination location, each node can send a signal to a node within an adjacent area. For example, the first node can send a signal to the second nodePCT Patent Application Attorney Docket Number: 47004-244178 when the first area is adjacent to the second area. Of course, other pathway variations are possible and disclosed below.

[0065] The nodes and the edge computing system / access point 130 may transmit signals (e.g., radio signals containing data related to a digital representation of information) to communicate with one another and the edge computing system / access point 130. The edge computing system / access point 130 may then communicate the same received digital representation of information to the remote database of the cloud network 145 as appropriate. For example, a first node within a first area may transmit the signal with the digital representation of information initially from its first area, or the current position of the node transmitting the initial signal. The signal may then either reach and be received by a dedicated communication node within the first area or reach and be received by a second node within a second area. From the first node or the first communication node, the signal may be sent to the second node because the first area is adjacent to the second area, and from the second node the signal may be sent to the third node because the second area is adjacent to the third area.

[0066] In some embodiments, the signals sent by the nodes or edge computing system / access point 130 may include multiple digital signals, multiple analog signals, or a combination of multiple digital and analog signals. In such embodiments, the multiple signals are combined into one signal using multiplexing protocols to reduce the resources required to send the signal. In an example embodiment, frequency division multiplexing (FDM) can be used to combine the signals. In another example, time division multiplexing (TDM) can be used to combine the signals. In yet another example embodiment, code division multiplexing (CDMA) can be used to combinePCT Patent Application Attorney Docket Number: 47004-244178 the signals. The receiver is supplied with the unique keys such that the receiver can identify the originating node. Other types of signal processing and data transmission protocols are envisioned and may be recommended within the disclosed system for assorted reasons.

[0067] In some embodiments, the signal may be sent via a packet switching process. In a packet switching process, the signal (e.g., the data being sent) is divided into smaller parts called packets. The packets are then sent individually from the source (e.g., the node or edge computing system / access point 130) to the destination (e.g., the second node or terminating at the edge computing system / access point 130). In some embodiments, each packet can follow a different path to the destination, and the packets can arrive out of order at the destination, where the packets are assembled in order (e.g., a datagram approach). In some embodiments, each packet follows the same path to the destination, and the packets arrive in the correct order (e.g., a virtual circuit approach).

[0068] The processor 220 of the edge computing system / access point 130 may comprise one or more processors 220 such as general-purpose processors (e.g., a single-core or multi-core microprocessor), special-purpose processors (e.g., an application-specific integrated circuit or digital-signal processor), programmable-logic devices (e.g., a field programmable gate array), etc. that are suitable for carrying out the operations described herein. The processor 220 may be a single-chip or multi- chip processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-PCT Patent Application Attorney Docket Number: 47004-244178 purpose processor 220 may be a microprocessor or any conventional processor, controller, microcontroller, or state machine. The processor 220 may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. In some embodiments, particular processes and methods may be performed by circuitry that is specific to a given function.

[0069] The edge computing system / access point 130 may also have a memory 225 (e.g., memory, memory unit, storage device). The memory 225 may contain one or more non-transitory computer-readable storage mediums, such as volatile storage mediums and / or non-volatile storage mediums. The memory 225 may also be integrated in whole or in part with other components of the system. The memory 225 may include one or more devices (e.g., RAM, ROM, EPROM, EEPROM, optical disk storage, magnetic disk storage or other magnetic storage devices, flash memory, hard disk storage, or any other medium) for storing data and / or computer code for completing or facilitating the various processes, layers, and circuits described in the present disclosure. The memory 225 may be or include transitory memory or non- transitory memory, and may include database components, object code components, script components, or any other type of information structure for supporting the various activities and information structures described in the present disclosure. According to an illustrative embodiment, the memory 225 may be communicably connected with the processor 220 and includes computer code for executing (e.g., by the processor 220) the processes, methods, and any stored executable software instructions described herein. While the memory 225 may bePCT Patent Application Attorney Docket Number: 47004-244178 local to the processor 220, it should be understood that the memory 225 (or portions of memory) could be remote from the processor 220, in which case the processor 220 may access such remote memory 225 through the network interface 215 (or some other network interface).

[0070] Memory 225 may store software programs or instructions that are executed by processor 220 during operation of the edge computing system / access point 130. For example, the memory 225 may include optimization logic, which can take the form of a plurality of instructions configured for execution by processor 220 for executing data processing commands of any software resident or accessible by the edge computing system / access point 130. The optimization logic may consider relevant attributes of the data received by the edge computing system / access point 130such as but not limited to the identification of the plurality of devices 115 on the network communications system 110, emission related information, and carbon- based information. The memory 225 may also store user input logic, which can take the form of a plurality of instructions configured for execution by processor 220 for receiving, processing, and delivering input data to the optimization logic to aid in the calculation, processing, and determination of any software applications resident or accessible by the edge computing system / access point 130. The memory 225 may also store request-handling logic, which can take the form of a plurality of instructions configured for execution by the processor 220 for controlling user access to manage and administer the edge computing system / access point 130, access to remote data resident on the cloud network 145 and its processing capabilities, information regarding the plurality of devices 115 on the network communications system 110, or information to be presented to others accessing the informationPCT Patent Application Attorney Docket Number: 47004-244178 processed within the system 110 and its potential display on a connected device. The request handling logic helps control how end users are granted access to the system 100, what information may be retrieved, and further how such information may be presented to such users.

[0071] The memory 225 may also be configured as a database or other storage 230 design where a plurality of identifiers may be stored associating potential users, cloud-based systems, and the plurality of devices 115 on the network communications system 110. Identifying information in further examples may also include login credentials that can be stored on the edge computing system / access point 130 and associated with a particular end user. Other memory addresses in the memory 225 can store a data structure related to information received by or to be transmitted from the edge computing system / access point 130. These data structures may further define the information contained within the data either pulled from outside databases (e.g. the cloud network 145) regarding analysis and reporting information associated with the agricultural environment 105 where the system 100 is deployed. These data structures may also define information contained within the data received from the plurality of devices 115 on the network communications system 110 that may be selected, examined, processed, or potentially reported to either the cloud network 145 or an end user accessing the system 100. Overall, these data structures may be employed and used as part of the optimization logic for the edge computing system / access point 130. The data structures resident on the edge computing system / access point 130 may be a single data structure or a plurality of data structures. It should also be understood that thePCT Patent Application Attorney Docket Number: 47004-244178 data structures may be fluid, reconfigurable, and change over time as the content of the memory 225 changes in the edge computing system / access point 130.

[0072] In some embodiments, the edge computing system / access point 130 may be configured to filter received signals from a node of the network communications system 110 that may contain certain types of digital information. For example, the edge computing system / access point 130 may receive a plurality of signals from multiple nodes of the network. The edge computing system / access point 130 may be configured to designate a subset of the plurality of signals in the manner of useful or not useful. For example, signals designated as useful may be relevant (e.g., complete, or of information requested / required by the edge computing system / access point 130) such that the edge computing system / access point 130 may clearly identify the coded information within the signal. A signal designated as not useful may be incomplete, irrelevant to edge computing system / access point tasks, or redundant. In some embodiments, a signal designated as not useful may include information of minor or inconsequential use by the edge computing system / access point 130 that is not going to be analyzed by the edge computing system / access point 130. In other embodiments, a signal designated as not useful may be a duplicate of another signal. A duplicate signal may include substantially the same information as another signal. A signal may be designated as a duplicate when the edge computing system / access point 130 determines that information from a first signal can be obtained from a second signal. The edge computing system / access point 130 may be configured to apply a threshold to determine whether a signal is a duplicate. For example, if a predetermined percentage (e.g., 90%) of the informationPCT Patent Application Attorney Docket Number: 47004-244178 from a first signal can be obtained from a second signal, the edge computing system / access point 130 may determine the first signal is duplicative.

[0073] Further, the edge computing system / access point 130 may be configured to ignore the subset of the plurality of signals designated as not useful. In one embodiment, the edge computing system / access point 130 may be configured to store 230 the subset of the plurality of signals that are designated as not useful in the memory 225 of the edge computing system / access point 130. Later, the edge computing system / access point 130 may be configured to perform further analysis, computations, processing, etc. on the subset designated as useful while not performing the analysis, computations, processing, etc., on the subset designated as not useful. This technological solution reduces the computational bandwidth needed to perform the systems and methods disclosed herein by reducing the quantity of computations the edge computing system / access point 130 performs by reducing the number of signals the edge computing system / access point 130 analyzes, processes, or computes.

[0074] In other embodiments, the edge computing system / access point 130 may be configured to delete or remove the subset of the plurality of signals that are designated as not useful. For example, the edge computing system / access point 130 can remove the subset of the plurality of signals that are designated as not useful from the edge computing system / access point 130. Along with reducing the computational bandwidth needed to perform the systems and methods disclosed herein, this technological solution reduces the amount of storage 230 needed to store and analyze the signals by removing the not useful signals from the edgePCT Patent Application Attorney Docket Number: 47004-244178 computing system / access point 130 for either processing operations or later communication to the cloud network 145.

[0075] Moreover, the edge computing system / access point 130 may be positioned at the terminus of the network communications system 110. The edge computing system / access point 130 may play a pivotal role in local data processing if requested. It is envisioned that possible devices, such as but not limited to, the PheNode, Raspberry Pi, or Jetson Nano, may be employed as part of the edge computing system / access point 130 and may be further configured to perform real- time carbon footprint calculations, general emissions data processing, or processing instructions useful to the overall system 100. The edge computing system / access point 130 may serve as the first point of analysis for preprocessing of data information received by the edge computing system / access point 130 from the plurality of devices 115 on the network communications system 110. This capability of the edge computing system / access point 130 may ensure low-latency decision- making and facilitate efficient data transmission to the cloud network 145 of remote databases. To accomplish this potential preprocessing, the edge computing system / access point 130 may be configured to parse data received by the plurality of devices 115 on the network communications system 110. The edge computing system / access point 130 may then be capable of a set of executable software instructions and calculations on the received data, such as but not limited to applying Global Warming Potential factors to a set of received data related to emissions within the agricultural environment 105. Further, the edge computing system / access point 130 can also categorize the resulting calculations of this data preprocessing by any applicable rule set resident or accessible by the edge computing system / accessPCT Patent Application Attorney Docket Number: 47004-244178 point 130. In some embodiments, the categorization by the edge computing system / access point 130 may involve separating and allocating this preprocessed data received by the plurality of devices 115 into defined tiers related to the relevant emissions type data analyzed. Implementing this tiered approach ensures a nuanced understanding of the carbon footprint's sources and impacts received by the edge computing system / access point 130 and relevant to the agricultural environment 105 where the system is deployed.

[0076] The edge computing system / access point 130 may adopt a two-pronged approach to data output. As a first output option, locally calculated or processed data may be accessible by end users authorized with the edge computing system / access point 130 or overall system 100 through a graphic user interface (GUI) on an electronic device associated with the end user. In some example embodiments, this may include data representing the local carbon footprint values of the monitored agricultural environment 105 and accessible to farm managers, workers, and others associated with the monitored agricultural environment 105. These end users can access such information through the graphic user interface (GUI) on an electronic device for immediate insights to relevant conditions currently present within the environment 105 and determined by the system 100. Simultaneously, the edge computing system / access point 130 may securely transmit the data received by the edge computing system / access point 130 from the plurality of devices 115 on the network communications system 110. The edge computing system / access point 130 may securely transmit this data, along with any preprocessing calculations performed at the edge computing system / access point 130 including any calculated results, to the cloud network 145 of remote databases. Within the cloud network 145,PCT Patent Application Attorney Docket Number: 47004-244178 this data, along with any preprocessing calculations performed at the edge computing system / access point 130 including any calculated results, can further undergo more in-depth analysis and be retained in a long-term storage location and format.

[0077] Within an example architecture of the network communications system 110, the computational processing ability of the edge computing system / access point 130 plays a key role. In one example architecture of an agricultural environment 105, the network communications system 110 may include one wireless edge computing system / access point 130 and perhaps one or more relays. The proposed architecture of the network communications system 110 integrates edge computing potential directly with the potential access point to the network. The edge computing system / access point 130 is not just an adjunct device, but a valued component equipped with processing power, memory 225, and storage 230. The edge computing system / access point 130 is designed to provide calculations for each localized and real-time analysis of potential emissions and carbon footprints within the environment 105. The system 100 of an internet-of-things communications network deployed within an agricultural environment 105 having a standard farm field setup may include a singular edge computing system / access point 130. In other embodiments, multiple edge computing systems / access points 130 may be implemented and used in the same setup. The edge computing system / access point 130 is responsible for managing the interplay between application requirements and network data, ensuring efficient data processing and communication.

[0078] The edge computing system / access point 130 may be equipped with a cellular interface 235. The edge computing system / access point 130 may further bePCT Patent Application Attorney Docket Number: 47004-244178 the primary link for communication with cloud network 145 of remote databases. This example architecture of the network communications system 110 provides centralized data processing and ensures efficient data exchange between the farm's local network and the cloud network 145. Here, the edge computing system / access point 130 acts as a centralization point for cloud network 145 interactions to facilitate streamline network performance and to support real-time agricultural decision- making.

[0079] In addition to the edge computing system / access point 130, a plurality of devices 115 may be present and deployed within the network communications system 110. The plurality of devices 115 may include specialized sensors 118, nodes / stations 120, relays / relay nodes 125, edge computing systems / access points 130, vehicles / machinery 135, drones 140, tracking devices, individuals, devices, smart phones, laptop computers, tablet computers, desktop computers, computing systems, and outside structures such as cellular towers, radio towers, base stations, base transceiver stations, etc., that are equipped for wireless and cellular communication. The plurality of devices 115 function as nodes or communication points within the network communications system 110. In some embodiments, this plurality of devices 115 can both transmit and receive signals to relay data and information along the network communications system 110. Any of the plurality of devices 115 that is connected to the network communications system 110 may at least transmit data to other nodes or the edge computing system / access point 130.

[0080] As viewed in Figure 3, one such example device of the plurality of devices 115 may be a node type unit referred to as a sensor / station 120. These sensors / stations 120 may be any type of electronic component that may be presentPCT Patent Application Attorney Docket Number: 47004-244178 to receive informational data from another device or object to which it is attached. Further, these sensor / station 120 may have the capability to transmit data captured or received by the sensor / station 120 to the network communications system 110 deployed within the agricultural environment 105. For example, the sensor / station 120 may be, but not limited to, an accelerometer, gyroscope, proximity sensor, light sensor, smart type device sensor, temperature sensor, motion sensor, security sensor, pressure sensor, humidity sensor, vibration sensor, a sensor contained within another object, a sensor added to monitor a specific data point of a legacy object, assistance type sensor, collision related sensor, soil sensor, moisture sensor, weather condition sensor, crop health sensor, emissions sensor, air quality sensor, water quality sensor, vehicle monitoring sensor, waste management sensor, fill-level sensor, smart type meter with a sensor, electricity use sensor, gas use sensor, and water use sensor, solar energy sensor, or sunlight sensor. In an example embodiment of the disclosure, the system 100 of an internet-of-things communications network deployed within an agricultural environment 105 may be most concerned with data and information obtains from a temperature sensor, humidity sensor, soil sensor, moisture sensor, weather condition sensor, crop health sensor, emissions sensor, air quality sensor, water quality sensor, smart type meter with a sensor, electricity use sensor, gas use sensor, or a water use sensor. These sensor / station 120 examples may provide the most relevant and useful data needed for later operations of the system 100 for the agricultural environment 105.

[0081] Figure 3 illustrates an example sensor / station 120 the plurality of devices 115 that may be located on a network communications system 110. Figure 3 illustrates multiple elements that may be present for operation of an examplePCT Patent Application Attorney Docket Number: 47004-244178 sensor / station 120. For example, the sensor / station 120 may first contain a sensing element 325. The sensing element 325 is a necessary component of the sensor / station 120 to detect physical or environmental changes associated with the defined implementation and use of the sensor / station 120. Further, the sensing element 325 can then convert these detections and changes observed by the sensor / station 120 into an electrical signal. The sensor / station 120 may also include a signal conditioning circuit 330. The signal conditioning circuit 330 can process the raw signal from the sensing element 325 to make it suitable for transmission to an outside network. In some possible embodiments, the signal conditioning circuit 330 may include amplifiers, filters, and converters to aid in the transition to an acceptable digital signal format. The sensor / station 120 may also include a processor 315. The processor 315 may be a microcontroller or microprocessor that interprets the conditioned signal and performs any necessary calculations defined and needed by the sensor / station 120. The processor 315 of the sensor / station 120 may be similar in use and functionality as described above with the processor of the edge computing system / access point 130. The processor 315 helps and prepares the received data by the sensor / station 120 for ultimate transmission. The sensor / station 120 may also have a memory 320 to store data temporarily before transmission. Additionally, the memory 320 may be used if the sensor / station 120 needs to retain calibration settings, configuration parameters, or employ firmware updates for use within a particular system 100. Also, the sensor / station 120 may have a power source 300. The power source 300 may be a battery or other power supply that powers the sensor / station 120. The power source 300 provides the necessary energy for all the components of the sensor / station 120 to function.PCT Patent Application Attorney Docket Number: 47004-244178

[0082] The sensor / station 120 may also include a wireless communication module 305. The wireless communication module 305 enables the sensor / station 120 to transmit data to a local network wirelessly. In some embodiments, the sensor / station 120 may be hardwired to the local network for data transmission. The wireless communication module 305 is envisioned to support various wireless protocols such as Wi-Fi, Bluetooth, or Zigbee. In an example embodiment, the wireless communication module 305 of the sensor / station 120 used with the disclosed network communications system 110 may utilize the modified Wi-Fi HaLow communication protocol. To communicate and transmit signals through the wireless communication module 305, the sensor / station 120 may have a communication interface 310 such as an antenna. The communication interface 310 assists with the wireless communication and any transfer of signals and data thereon. The communication interface 310 may be connected to the wireless communication module 305 to send and receive signals associated with or useful to the sensor / station 120 within a particular architecture of the network communications system 110. Generally, within the sensor / station 120, data flows from the sensing element 325, through the signal conditioning circuit 330, and processor 315. Lastly, the data flows to the wireless communication module 305 for transmission with any present communication interface 310.

[0083] The network communications system 110 can utilize a diverse array of sensors / stations 120 strategically incorporated and placed across agricultural equipment and fields of the environment 105. In some example embodiments, these sensors / stations 120 may include exhaust gas analyzers, power meters, GPS trackers, or the like. Each of these sensors / stations 120 are designed for specificPCT Patent Application Attorney Docket Number: 47004-244178 types of data collection pertinent to emissions and carbon emission tracking. This comprehensive approach to data gathering is a significant advancement over traditional sensor networks. The role of these sensor / station 120 as part of the plurality of devices 115 on the network communications system 110 is to capture emissions data, electricity consumption patterns, and respective location information. Afterwards, the captured data is transmitted appropriately on the network communications system 110. In some embodiments, the sensors / stations 120 may execute preprocessing applications on the captured data before transmission to the network communications system 110.

[0084] Figure 3 also illustrates the potential data flow process within a typical sensor / station 120 or GPS unit that may be employed as part of the network communications system 110. The general process can be broken down into four primary stages. At a first stage, the sensor / station 120 or GPS unit may utilize signal conditioning circuit 330 having an internally present analog-to-digital converter (ADC). Here, the sensor / station 120 or GPS unit captures environmental data via the sensing element 325 related to the object, task, or assignment it is dedicated to perform within the monitored agricultural environment 105. This first stage data of a sensor / station 120 may include receiving various measurements like temperature, humidity, or soil moisture. For a GPS unit, the first stage data may include receiving geolocation data. The analog-to-digital converter (ADC) within signal conditioning circuit 330 is crucial for converting analog signals (environmental measurements or GPS signals) into a digital format that can be processed further by later component of the system 100.PCT Patent Application Attorney Docket Number: 47004-244178

[0085] At the second stage, use of the microprocessor 315 with a memory 320 occurs with each the sensor / station 120 and GPS unit. Digital data converted in stage one by the sensor / station 120 or GPS is then transmitted to the microprocessor 315 and memory 320. The microprocessor 315 is responsible for the initial processing of the data and the memory 320 for temporary storage of the data. The internal microprocessor 315 performs tasks such as data filtering, preliminary analysis, and formatting as required and instructed.

[0086] At the third stage, the sensor / station 120 or GPS unit instructs use of its wireless communication module 305 or wireless transceiver. In some embodiments, the wireless communication module 305 of the sensor / station 120 or GPS unit is configured to communicate on a modified Wi-Fi HaLow communications protocol. The processed data is transmitted wirelessly via a Wi-Fi HaLow-based transceiver as the wireless communication module 305. At this stage, use of the modified Wi-Fi HaLow technology is recommended as the implemented communications protocol since it provide long-range and low-power benefits compared to alternative communications protocals. Thus, use of the modified Wi-Fi HaLow technology is beneficial and preferable for agricultural environments 105 of the system 100 as the sensors / stations 120 may be spread over large geographical areas.

[0087] The fourth stage implements all the above processes and provides additional benefits. The fourth stage can be generally called use of the power source 300. Integral to implementation of the above process for these sensors / stations 120, or GPS units, is operational use of the power source 300. The power source 300 supplies energy to the entire sensor / station 120 or the GPS system to which it is connected. The power source 300 is designed to be an energy-efficient supplier.PCT Patent Application Attorney Docket Number: 47004-244178 Thus, the power source 300 works and aligns with the low-power nature of Wi-Fi HaLow technology. The power source 300 further ensures that sensors / stations 120 can operate for extended periods without frequent battery replacements or charging. This is recommended and beneficial to the system 100 the location of these sensors / stations 120 in the environment 105 may be found in remote or less accessible farm areas, yet consistent data collection is needed for optimal monitoring.

[0088] This comprehensive data flow process regarding these sensors / stations 120 or GPS units, from acquisition to wireless transmission, underpins the effective functioning of the system 100 of an internet-of-things communications network deployed within an agricultural environment 105. The data flow process and staged implementation ensures that data is not only accurately captured but also efficiently processed and transmitted with optimized power usage.

[0089] For objects with GPS units as their sensors / stations 120, these units may have additional capabilities and allowable communications tactics that can be used and accessed by the system 100 employed within an agricultural environment 105. In some instances, monitored GPS units of the network communications system 110 may be found outside of the monitored agricultural environment 105. This leads to such GPS units being unable to connect to the local area network of the network communications system 110 they generally use to report relevant data. However, these GPS units can still operate as part of the system 100 and the network communications system 110. Via cellular network communication found in these GPS units, the GPS units can report information and data associated with the operation of the object they monitor back to the remote databases via the cloudPCT Patent Application Attorney Docket Number: 47004-244178 network 145 when the local area network connection is unavailable. In these situations, the remote databases accessible through the cloud network 145 will return aggregated data collected from GPS devices outside the monitor agricultural environment 105 to the edge computing system / access point 130 for further aggregation and calculation. Additionally, GPS-equipped devices such as tractors or drones collect real-time location data (latitude, longitude, and time) while operating within the monitor agricultural environment 105. The system 100 may operate so that this data is periodically transmitted to the edge computing system / access point 130 via the Wi-Fi HaLow network. The timing of such a data transfer is adjustable and can be set to real-time or daily intervals based on user needs. At the edge computing system / access point 130, raw GPS data undergoes preprocessing for error filtering, normalization, and structuring. The edge computing system / access point 130 may then calculate metrics like distance traveled or area covered by analyzing the changes in geographic coordinates. This processed data could then be sent to remote databases through the cloud network 145 for advanced analysis, where the GPS related data will be integrated with other environmental data to calculate the carbon footprint. Such other environmental data examples and factors include, but are not limited to, considering machinery operation duration and type. The cloud network 145 of remote databases may analyze the results of these data analytics calculations including any GPS data and determine any carbon footprint metrics. Those output and results may then be made available for real-time or daily access by end users such as farm managers. Additionally, the cloud network 145 of remote databases provides feedback to the edge computing system / access point 130 and can further update models or parameters for enhanced data accuracy andPCT Patent Application Attorney Docket Number: 47004-244178 processing efficiency. This process exemplifies a comprehensive approach to GPS data management within the internet-of-things communications network system 100 and emphasizes real-time data utility and integration for emissions related data operations including carbon footprint calculations.

[0090] The sensors / stations 120 of the system 100 are designed to withstand the rigors of agricultural environments 105. Robustness and durability are paramount for any sensors / stations 120 deployed in this system 100 and as part of the plurality of devices 115 on the network communications system 110. Utilizing robust and durable sensors / stations 120 ensures continuous and accurate data collection despite exposure to varying weather conditions and mechanical vibrations that are present and common in an agricultural environment 105.

[0091] In the network communications system 110, crucial roles are played by each the sensors / stations 120, edge computing systems / access points 130, and relays 125. The sensors / stations 120 are strategically deployed throughout the agricultural environment 105 to capture a wide range of data, including emissions, climate conditions, and soil health. These sensors / stations 120 are the primary data collection points and are designed to operate efficiently in the diverse environmental conditions of an agricultural environment 105. The data collected by these sensors / stations 120 is then transmitted to edge computing systems / access points 130, relays 125, or gateways. These devices may be equipped with a specific wireless communication protocol technology, such as modified Wi-Fi HaLow technology, enabling them to receive data over long distances while conserving power. These devices serve as the first point of data processing and may further perform tasks like data filtering, aggregation, and preliminary analysis. This networkPCT Patent Application Attorney Docket Number: 47004-244178 communications system 110 setup reduces the need for continuous data transmission to central servers to save bandwidth and minimize latency. Additionally, the network communications system 110 may include relays 125 as nodes which help extend the network's range and ensure consistent data transmission even in remote or obstructed areas of the monitored agricultural environment 105. These relays 125 are essential for maintaining a robust and resilient network infrastructure. Generally, the network communications system 110 may employ a mesh network architecture. The mesh network architecture ensures resilient connectivity and data transmission across the agricultural landscape. This mesh network architecture allows for multiple communication paths, enhancing the network communications system’s reliability and robustness.

[0092] Another component of the network communications system 100may be a relay 125 as viewed in Figure 4. Figure 4 displays the architecture of a relay 125 or relay node in the network communications system 110 that may be used, in some embodiments, with a modified Wi-Fi HaLow (IEEE 802.11ah) communications protocol. Like the sensors / stations 120 and edge computing systems / access points 130, the relay 125 is usefully deployed in the system 100. Each relay 125 features a power unit 400 for sustained operation. The relay 125 features also include wireless transceivers 405 that may be configured to operate on the modified Wi-Fi HaLow communications protocol. Further, the relay 125 can include a processor 415 for managing all wireless communications. The relay 125 may further possess a built-in memory 420 with storage 425 capabilities. This memory 420 and storage 425 are useful for aggregating and buffering data collected from multiple sensors attached stations (STAs). This network communications system architecture with relays 125PCT Patent Application Attorney Docket Number: 47004-244178 not only ensures reliable data transmission across vast agricultural fields but also contributes to the overall efficiency and resilience of the network communications system 110.

[0093] In some embodiments, the relay 125 is a more complex entity comprising three main components: a relay access point, a relay function, and a relay station (sensor / device). The relay function is responsible for forwarding data received from other devices or sensors / stations 120 within the network. In some examples, the relay station may further function like a potential sensor / station device to provide data associated with a particular object. Yet here, the relay station is uniquely associated with the edge computing system / access point 130 or a second access point. This design allows the relay 125 to effectively bridge communication between the sensor / station devices and the access points to ensure efficient data transmission within the network communications system 110.

[0094] Figures 5 and 6 illustrate potential implementation designs that may be associated with components of the network communications system 110 to create a beneficial mesh network architecture. The network communications system 110 may utilize a modified Wi-Fi HaLow communications protocol. A modified Wi-Fi HaLow communications protocol offers long-range capabilities. Those capabilities are harnessed to ensure that sensors / stations 120 scattered across vast agricultural fields maintain connectivity. GPS trackers assist in precise location tracking, optimizing route planning, and enhancing overall system efficiency. Existing solutions such as LoRA, NB-IoT, and SigFox may appear to offer long-range communication feasibility (i.e., more than 1 km) but these communication protocols suffer from low data rates and limiting scalability. Wi-Fi, BLE, and 6LoWPAN mayPCT Patent Application Attorney Docket Number: 47004-244178 also seem to offer usable technology with higher data rates. However, use of these protocols lead to a limited area of coverage. Additionally, 4G / 5G cellular networks also have limited coverage, higher energy consumption, and cost. Use of a modified Wi-Fi HaLow communications protocol bridges this gap by constructing a network having the potential to interconnect over eight thousand devices covering a range of more than 1 km and offers a solution not yet present or available within the agricultural environments.

[0095] As can be viewed in Figures 5 and 6, the network communications system 110 employs a mesh network architecture to enable multiple communication paths between nodes. This redundancy enhances the network communications system’s resilience to connectivity disruptions, which are a critical factor in remote and dynamic agricultural landscapes / environments.

[0096] When implementing the system 100 of an internet-of-things communications network deployed within an agricultural environment 105, there may be a placement strategy employed with the location of relays 125 or relay nodes. Figure 5 illustrates the position of relays 125 and sensors / stations 120 (STA) association with edge computing systems / access points 130 and relays 125. Figure 6 illustrates an angular separation-based relay placement strategy 600. For expansive agricultural environment areas, strategically placing relays 125 or relay nodes is essential for comprehensive network coverage. Farms or agricultural environments typically spanning 1 to 2 square kilometers present a diagonal stretch of about 1.4 to 2.8 kilometers. In such a configuration, the central edge computing system / access point 130 is ideally positioned at the farm's midpoint. The location of this edge computing system / access point 130 is recommended to ensure maximum coverage. With usePCT Patent Application Attorney Docket Number: 47004-244178 of the modified Wi-Fi HaLow capability of one kilometer per hop, placing a relay 125 or relay node at an optimal halfway point effectively extends this coverage. Thus, it may be possible to ensure reliable connectivity across the farm or agricultural environment, including any remote areas.

[0097] The optimal number of relays 125 or relay nodes that may be present within the network communications system 110 should also be considered. The optimal number of relays 125 or relay nodes for complete farm / field / agricultural environment coverage is determined by angular separation 630 and the modified Wi-Fi HaLow’s coverage range. When utilizing this technology via a single-hop setup, the angular separation (^^^^) 630 is used to efficiently position relays 125 or relay nodes around the central edge computing system / access point 130. For example, the efficient positional placement of the relay 125 or relay node can be calculated with the following equation.

[0098] In this equation, it should be understood that d is the wireless distance between the relay 125 and edge computing systems / access points 130, and C is the relay coverage. This equation-based methodology ensures gap-free coverage across the farm / field / agricultural environment. In a two square kilometer farm, it may be possible and typical for relay use in one hop. However, larger, or irregularly shaped farms / fields / agricultural environments may require more nodes. The number of required relays 125 or relay nodes for the hthhop may be calculated using the below equation to ensure efficient network scalability and robust coverage.PCT Patent Application Attorney Docket Number: 47004-244178

[0099] As stated earlier, the plurality of devices 115 on the network communications system 110 may communicate with one another via a select communications protocol. In an example embodiment, the wireless communication protocol may be a modified Wi-Fi HaLow communications protocol. Figure 7 illustrates a proposed protocol stack 700 for this modified Wi-Fi HaLow communications protocol. The proposed protocol stack 700 for the modified Wi-Fi HaLow communications protocol used within the system 100 of an internet-of-things communications network deployed within an agricultural environment 105 can be visualized to note a carefully structured framework designed to optimize communication and data processing. This is done and occurs above the MAC and PHY layers of 802.11ah in Figure 7. At the foundation link layer 720, the 802.11ah standard provides a dependable physical (PHY) and medium access control (MAC) layer. Thus, these stack components fit and are tailored for long-range and low- power network communications with a plurality of interconnected devices and applications. Building upon this, the proposed protocol stack 700 and overall network communications system employs the IPv6 over Low-power Wireless Personal Area Networks (6LoWPAN) as part of the network layer 715. This protocol facilitates efficient IP-based communication over resource-constrained devices. In turn, it becomes a promising selection for agricultural network communications with a plurality of interconnected devices / applications / setups.

[0100] As for routing associated with the modified Wi-Fi HaLow communications protocol, a dynamic protocol is proposed to enhance the overall system’s ability toPCT Patent Application Attorney Docket Number: 47004-244178 adapt to changing network conditions and optimize data paths. At the transport layer 710, both UDP and TCP are supported to offer flexibility in data transmission. UDP allows for quick, real-time communication, while TCP ensures dependable and ordered delivery of data packets. Finally, at the application layer 705, protocols like Constrained Application Protocol (CoAP) and Message Queuing Telemetry Transport (MQTT) are further incorporated into the proposed protocol stack 700. These protocols support diverse data formats and enable efficient, scalable communication between a plurality of interconnected devices and any end server. This use aligns with the diverse and dynamic nature of agricultural data and operations needed to implement the system 100 of an internet-of-things communications network deployed within an agricultural environment 105.

[0101] To implement the modified Wi-Fi HaLow communications protocol used within the system 100, a specific driver may be design and selected for use with the appropriate communication modules associated with each of the plurality of devices 115 that may be present on the network communications system 110. Such a driver may be specifically designed for Wi-Fi HaLow use and implementation. This driver may provide the needed foundation for the internet-of-things communications system 100 by offering robust support tailored to the unique requirements of Wi-Fi HaLow technology. Utilizing this driver design, the proposed system may be constructed in a reliable manner facilitating smooth integration and optimal performance of the various components involved with any type of communications tasks or calls.

[0102] Further, such a driver for use of the modified Wi-Fi HaLow communications protocol allows further features such as customization and enhancement of any associated driver software advancements or updates. Thus, this driver can and isPCT Patent Application Attorney Docket Number: 47004-244178 proposed to be configured to the specific needs of the internet-of-things communications system 100 deployed within an agricultural environment 105. Moreover, such a driver is proposed to streamline proposed implementation and future development as it would guarantee compatibility with existing Wi-Fi HaLow standards, ensuring system stability and reliability, and proposed effective use in real-world applications.

[0103] The proposed driver is envisioned to be modified for use with the internet-of- things communications system 100 in an agricultural environment 105, and to be specifically tailored to meet those needs and demands of the system’s operation. As such, modifications are proposed and implemented at the driver level to implement specific software with functionality leading to increased and optimized network performance. This software code may further include a computational algorithm central to optimizing network performance, particularly in effectively managing the traffic load across different sensors / stations 120 of the plurality of devices 115. There is currently a lack of native support for the 802.11ah MAC / PHY layer used with the Wi-Fi HaLow communications protocol. The 802.11ah MAC / PHY layer is needed for seamless communication in the overall system’s proposed mesh and dynamic routing network.

[0104] To address this, a solution was created and developed using an advanced 6LoPWAN adaptation layer. This advanced 6LoPWAN adaptation layer of the network layer 715 will incorporate necessary fragmentation and compression techniques for data frames, enabling interoperable communication using upper-layer protocols such as IPv6, UDP, and CoAP. The implementation of this adaptation layer is recommended and optimal for ensuring efficient data transmission andPCT Patent Application Attorney Docket Number: 47004-244178 compatibility across various network components. This improvement enhances the overall functionality and robustness of the modified Wi-Fi HaLow communications protocol. These advancements not only cater to the immediate requirements of the internet-of-things communications system 100 but also set a foundation for future innovations in internet-of-things network communications.

[0105] To execute the above advancement, software having a set of executable code instructions can be implemented on the communications modules of the plurality of devices 115 that may communicate with the modified Wi-Fi HaLow communications protocol on the network communications system 110. In the proposed system 100, managing network traffic efficiently is crucial, especially given the varying loads over time. The executable system advancement addresses potential congestion issues in different communication groups (known as RAW groups) due to fluctuating traffic. It further prioritizes certain types of traffic to ensure smooth operation. Implementation of this advancement can be viewed within Figures 9 and 10 and described in further detail below. To achieve this, the system 100 now dynamically groups sensors / stations 120 (or nodes) based on their current data load and priority.

[0106] Grouping with the modified Wi-Fi HaLow communications protocol improves channel utilization and enhances network scalability. This is needed for efficient management of large-scale deployments such as an internet-of-things environment with many communications ready devices connected to and deployed upon a network. The internet-of-things communications system 100 for an agricultural environment 105 makes logical groups of similar types of devices of the plurality of devices 115. For example, related devices via agricultural function, data monitoringPCT Patent Application Attorney Docket Number: 47004-244178 capabilities, or complex multilevel operations may be grouped together. As an example, drones 140 or unmanned aerial vehicles may be a grouping, agricultural equipment another grouping, and GPS enabled devices yet another grouping with this structure. However, it should be understood that any initial groupings may change when a RAW group is heavily loaded, and rebalancing of network traffic is needed.

[0107] Here, the network processing tasks, such as managing communication and data flow, are primarily managed by the access points 130 and relays 125, with relays 125 also functioning in a relay access point mode. In some embodiments the edge computing system may also aid with this functionality. However, it is envisioned that the edge computing systems, which are attached to the access point 130, are generally dedicated to processing data-related tasks that are generally received from the data signals sent by the sensors / stations 120 within the network. Those tasks generally include analyzing and interpreting the information received from the network.

[0108] The system calculates the load (amount of data to be transmitted) for each RAW group, considering both the regular and priority traffic. The goal is to balance this load across diverse groups to prevent any group from becoming too congested. This load balancing is crucial for maintaining the network's efficiency and ensuring that all data, especially high-priority traffic, is transmitted reliably and on time.

[0109] Optimization of channel utilization and dynamic station grouping may be accomplished in a few diverse ways. Further disclosure and information on how communications through channel and station optimization can be implemented may be viewed in Appendix A of U.S. provisional application serial number 63 / 572,818 toPCT Patent Application Attorney Docket Number: 47004-244178 which this PCT application claims priority. Appendix A is an article titled SoftFarmNet: Reconfigurable Wi-Fi HaLow Networks for Precision Agriculture wherein the disclosure of such is incorporated herein by reference and within U.S. provisional application serial number 63 / 572,818. Figure 8 illustrates possible slot allocation within the modified Wi-Fi HaLow communications protocol network associated with the plurality of devices communication on the network. This allocation effectively categorizes traffic from the plurality of devices, or any internet- of-things network devices, into three classes - automation-related, periodic, and on- demand. These allocations are then assigned priority levels wherein automation- related tasks are assigned the lowest priority, periodic tasks are assigned intermediate priority, and on-demand tasks are assigned the lowest priority. This prioritization is pivotal in meeting the Quality of Service (QoS) requirements and efficient resource allocation within the internet-of-things communications system 100 deployed within an agricultural environment 105. Internet-of-things sensors / stations 120 within an agricultural environment 105 are primarily tasked with periodic updates on carbon or emissions based footprinting and are thus designated the intermediate priority level. This classification aligns with their operational frequency and the criticality of their data for sustainable agricultural practices.

[0110] To accurately determine the periodicity of agriculturally based internet-of- things data flows, especially when such periodicity is not predefined at the access point (AP) 130, the autocorrelation function method is employed by the system. This approach ensures that the network dynamically adjusts to the traffic patterns of agriculturally based internet-of-things nodes, thereby optimizing the scheduling of data transmission and reducing unnecessary wake-up calls for the devices. ThisPCT Patent Application Attorney Docket Number: 47004-244178 strategy is not only efficient but also aligns with the goal of minimizing the carbon footprint by conserving energy at the sensor / station nodes 120.

[0111] Figure 8 illustrates the slot allocation process 800 tailored for periodic agriculturally based internet-of-things traffic 825. In the proposed scheme, it is assessed whether the periodicity T_p is greater than or equal to the DTIM interval 830. If this condition is met 840, a dedicated slot is scheduled in a RAW group following the T_dtim interval. If the periodicity T_p is shorter than the DTIM interval, the scheduling is performed according to the association identifier (AID) mapped RAW 835, ensuring optimal resource allocation and efficiency in data transmission.

[0112] Further, Figure 9 illustrates possible traffic load-based dynamic grouping 900 for avoiding congestion in agriculturally based internet-of-things communications. Further disclosure and information on how traffic load-based dynamic grouping may be implemented to avoid congestion can be viewed in Appendix A of U.S. provisional application serial number 63 / 572,818 to which this PCT application claims priority. Appendix A is an article titled SoftFarmNet: Reconfigurable Wi-Fi HaLow Networks for Precision Agriculture wherein the disclosure of such is incorporated herein by reference and within U.S. provisional application serial number 63 / 572,818. The agriculturally based internet-of-things traffic, characterized by its periodic nature, is given higher priority over on-demand traffic flows, particularly in scenarios where the RAW group is experiencing high load 910. This prioritization is managed by reallocating stations tasked with uploading on-demand data to different RAW groups. The reallocation strategy is guided by a particular channel utilization factor, which plays a crucial role in dynamically assigning association identifiers (AIDs) 925 to optimize channel usage and balance the network load. Figure 9 illustrates thisPCT Patent Application Attorney Docket Number: 47004-244178 dynamic AID allocation process, where the traffic load in a RAW group (L_raw) is continuously monitored 915. Stations are reassigned as needed to distribute the load more evenly across the network, thereby maximizing channel utilization 930 and maintaining efficient data transmission for both periodic agriculturally based internet- of-things and on-demand traffic.

[0113] The following examples are illustrative examples of how data originating at a node may flow through different pathways based on the groupings / priority / load of the overall system. In the disclosed agriculturally based internet-of-things architecture, the data flow from a node is intelligently managed based on network dynamics. It may unfold in the manner disclosed below, but it should be understood additional pathways and approaches can also be utilized.

[0114] In the first example, data originates at a node or device of the plurality of devices 115 on the network communications system 110. For example, a sensor in the agriculturally based internet-of-things network collects specific data, like carbon emissions from a farm or monitored agricultural environment area. This data is readied for transmission. The node identifies its transmission window through delivery traffic indication message (DTIM) and traffic indication map (TIM) mappings 810. Identification in this manner eliminates the need for conventional contention mechanisms.

[0115] Next, node association and initial grouping processes may be performed. The node determines its closest connection point, which can be either a relay 125 or an access point (AP) 130. The determination may be made based on signal strength. In the case of a relay node 125, the data is forwarded to the access point 130 where the relay operates in a station mode 120. The edge computing system 130,PCT Patent Application Attorney Docket Number: 47004-244178 integrated with the access point 130, classifies the incoming data. The data is then identified as agriculturally based internet-of-things traffic 815. The access point or edge computing system then prepares future RAW parameter sets with this information.

[0116] Then, dynamic load assessment and group reassignment may occur. In this functional operation, the edge computing system / access point 130 constantly evaluates the load across different RAW groups 910. If a group designated for the sensor’s data transmission becomes overloaded 915, the system dynamically shifts the sensor node to a less congested group, thus optimizing data transfer efficiency and reducing delays.

[0117] Finally, tasks related to transmission and processing are to follow. At this point, the data is then transmitted to the edge computing system / access point 130 or remote databases of the cloud network 145 for processing. The pathway for this transmission is chosen to ensure the fastest and most efficient delivery. As outlined above, this is accomplished and based on the current network conditions and data priorities.

[0118] Within the software system 148 subpart of system 100 for an internet-of- things communications network deployed within an agricultural environment 105, there is an associated data flow path wherein the data may be subject to further data processing applications related to software contained and stored by components of the system 100. Figure 10 presents a depiction of the data flow 1000 within the system 100 as an internet-of-things communications network deployed within an agricultural environment 105. Generally, an agricultural environment 105, equipped with a variety of sensors / stations 120 and tracking devices, serve as the primaryPCT Patent Application Attorney Docket Number: 47004-244178 data sources 1005 and inputs for the system 100. These agricultural environments 105 are also fitted with actuators that receive commands from processing units at both the edge computing system / access point 130 and the remote databases of the cloud network 145. Also, the graphical user interface (GUI) 1020 plays a vital role. The graphical user interface 1020 may provide user-driven controls and insights based on a combination of human intelligence and system-generated data. The data flow from the graphical user interface 1020 is akin to that from the edge computing system / access point 130 and the remote databases of the cloud network 145 to ensure seamless integration. Decisions generated by the overall system 100 may be automated and based on data processed at two levels. At a first level limited yet immediate processing at the edge computing system / access point 130 is possible for quick and actionable responses. At a second level, more extensive, in-depth analysis can be accomplished within the remote databases of the cloud network 145 for strategic decision-making related to the monitored agricultural environment 105.

[0119] Various software applications may be present or called by the system 100 as an internet-of-things communications network deployed within an agricultural environment 105. The breakdown of these software storage locations of the software system 148, as well as the locations where these software modules may be executed, is not without thought. The software applications’ placement and functionality is structured into several key routines and subroutines. Figure 11 illustrates information regarding subprocesses and routines 1100 that may be present within the system 100 as an internet-of-things communications network deployed within an agricultural environment 105. Each routine and subroutine may be tailored to specific functions. For example, the data collection subroutine 1105 isPCT Patent Application Attorney Docket Number: 47004-244178 responsible for gathering sensor data and ensuring data integrity before transmission. As another example, in the data preprocessing subroutine 1110, data undergoes filtering, normalization, and error correction to prepare the data for analysis. The example carbon footprint calculation subroutine 1115 is present and plays a key role. The carbon footprint calculation subroutine 1115 applies appropriate emission factors across different tiers of associated sensor data (Tier-1, Tier-2, Tier-3) to compute the carbon or emissions footprint accurately. Advanced data analysis may also be conducted in the example cloud data analysis subroutine 1125 after data transmission 1120 to the cloud network 145. Here, aggregated data is subjected to potential artificial intelligence processing and machine learning algorithms to extract valuable insights from the data. Lastly, the example user interface management subroutine 1130 facilitates interaction between users and the system 100. The user interface management subroutine 1130 allows for displaying data and assimilating user inputs for requested or desired system updates. Together, these components form a cohesive and comprehensive software system 148 that accomplishes efficient operation and decision-making in sustainable agricultural practices when applied by the system 100 as an internet-of-things communications network deployed within an agricultural environment 105.

[0120] Implementing the system 100 as an internet-of-things communications network deployed within an agricultural environment 105 having these software modules and routines offers multiple benefits to the end users of the system 100. As a first benefit, execution of these software modules and routines, algorithms, and processing provide real-time data analysis. The software system 148 is designed for the real-time analysis of sensor data obtained by the plurality of devices 115, andPCT Patent Application Attorney Docket Number: 47004-244178 this real-time analysis allows for timely and accurate monitoring of conditions. This capability represents a substantial improvement in data processing speed and efficacy over anything currently employed in and agricultural ecosystem. As a second benefit, execution of these software modules and routines, algorithms, and processing provides a distributed processing approach cognizant of both the value of obtained data as well as consideration of system resources. The system 100 employs a distributed processing model where data is analyzed both at the edge computing system / access point 130 (for immediate insights) and within the remote databased of the cloud network 145 (for comprehensive analysis). This hybrid approach optimizes data processing efficiency and scalability. As a third benefit, execution of these software modules and routines, algorithms, and processing provide for the application of advanced machine learning algorithms on retrieved and reported data by the system 100. Incorporating sophisticated machine learning algorithms for predictive analytics and decision support is a significant enhancement. This allows for more nuanced and accurate predictions based on a variety of data inputs. Finally, as a fourth benefit, execution of these software modules and routines, algorithms, and processing provide a user-friendly interface 1020 for favorable and simple interactions and implementations of requests. The development of an intuitive, user-friendly graphical user interface 1020 may be tailored for agricultural specific users. The graphical user interface 1020 may further simplify the needed interaction with complex data sets and analytics, and potentially remove any requirement to do so. Thus, the graphical user interface 1020 of the system 100 can be largely accessible and understandable for practical agricultural decision-making and issue spotting. Also, this user-friendly interface 1020 provides real-time insightsPCT Patent Application Attorney Docket Number: 47004-244178 into locally calculated carbon footprint values that matter to local farmers and workers. The graphical user interface 1020 allows users to visualize and interpret the data, enabling informed decision-making for sustainable farming practices.

[0121] Generally, the software modules and applications of the software system 148 subpart of the system 100 as an internet-of-things communications network deployed within an agricultural environment 105 can be implemented either at the edge computing systems / access points 130 or at the remote databases of the cloud network 145. Of course, there may be, and it is envisioned, that other locations within the system 100 may perform some or all the following software application processing and computational tasks.

[0122] The edge computing systems / access points 130 may first perform and execute some of the resident software applications of the internet-of-things communications system 100 used within an agricultural environment 105. This may include preprocessing of data it has received from the local monitored agricultural environment 105 to which the edge computing system / access point 130 is connected and communicated to it by the plurality of devices 115 on the network communications system 110.

[0123] Figure 12 illustrates a preprocessing algorithm 1200 of executable code that can be implemented at the edge computing system / access point 130. Of course, it should be understood that this algorithm may be stored and accessed from other locations within the network communications system 110 or executed at a different location than the edge computing system / access point 130. The Figure 12 flowchart presents the steps involved in preparing raw sensor data for analysis at the edge computing level of the complete system 100. The preprocessing algorithm 1200PCT Patent Application Attorney Docket Number: 47004-244178 emphasizes filtering, normalization, and error checking processes, crucial for ensuring data accuracy before later carbon footprint calculation. The preprocessing algorithm 1200 refines the dataset, making it suitable for accurate analysis, and is crucial for maintaining data integrity within the system 100.

[0124] In an agricultural setting utilizing the internet-of-things communications system 100 monitoring an agricultural environment 105, the first algorithm for data preprocessing 1210 is applied to sensor data for monitoring carbon emissions. It can also be used and adjusted to monitor other related conditions that may occur and wish to be tracked within the monitored agricultural environment 105. This algorithm 1210 involves sensors like CO2, CH4, and N2O emission detectors strategically placed across the monitored agricultural environment 105 capable of capturing raw analog signals indicative of gas concentrations. The preprocessing at the edge computing system level starts with filtering 1220 any noise and / or irrelevant data. Noise and / or irrelevant data may include emissions from non-agricultural sources or temporary, unrelated spikes. The data is then normalized 1225, converting various gas concentration readings into a consistent format and scale. This is done to ensure uniformity across different sensor types for integrated analysis. Error checking 1230 is another key step. Error checking 1230 identifies and rectifies anomalies or inconsistencies in the data, like unexplainable spikes in emission levels, or handling outliers. Finally, the algorithm compiles 1235 this filtered, normalized, and error- checked data into a clean, structured dataset, ready for subsequent carbon footprint calculations or other emissions related uses. This meticulous preprocessing 1200 ensures accuracy and reliability, which is vital for making informed decisions about sustainable farming practices and emission control.PCT Patent Application Attorney Docket Number: 47004-244178

[0125] Figure 13 illustrates a tier-1 carbon footprint calculation algorithm 1300 of executable code that can be implemented at the edge computing system / access point 130. Execution of the calculation algorithm 1300 may or may not occur precisely at the edge computing system / access point 130 and may involve feedback with the remote databases in the cloud network 145. Of course, it should be understood that the calculation algorithm 1300 algorithm may be stored and accessed from other locations within the network communications system 110 and further executed at a different location than the edge computing system / access point 130. The following presents an example scenario where the tier-1 carbon footprint calculation algorithm 1300 may be utilized and executed by the edge computing system / access point 130.

[0126] As representative of its use within system 100, suppose there exists a monitored agricultural environment 105 equipped with various machinery including tractors and harvesters. Each piece of machinery is fitted with sensors to measure emissions of CO2, CH4, and N2O 1318 during operation. It may be assumed the following data collected over a specific period for the purposes of understanding the application and use of the tier-1 carbon footprint calculation algorithm. Tractor CO2 Emissions: 120 kg Harvester CO2 Emissions: 80 kg Tractor CH4 Emissions: 5 kg Harvester CH4 Emissions: 3 kg Tractor N2O Emissions: 1 kg Harvester N2O Emissions: 0.5 kg

[0127] Global Warming Potential (GWP) factors (as per IPCC guidelines) for these gases may be provided as cloud-based updates 1320 and 1322 regarding any appropriate changes to such values. These updates would be periodically communicated by the remote databases in the cloud network 145 and received atPCT Patent Application Attorney Docket Number: 47004-244178 the edge computing system / access point 130 to update the tier-1 carbon footprint calculation algorithm 1300. These Global Warming Potential (GWP) factors may be the following example values: GWP_CO2 = 1 GWP_CH4 = 25 GWP_N2O = 298

[0128] Having now obtained both recorded sensor values 1318 and the values 1322 needed regarding the Global Warming Potential (GWP) factors, the tier-1 carbon footprint calculation process may commence in the following manner. First, the tier-1 carbon footprint calculation algorithm 1300 will aggregate the total emissions for each gas across all machinery. Second, the tier-1 carbon footprint calculation algorithm 1300 will be applying the GWP factors to convert all emissions into CO2-equivalents 1325. Then, the tier-1 carbon footprint calculation algorithm 1300 will sum up these equivalents to get the total tier-1 carbon footprint recorded and received by the associated sensor data.

[0129] To further illustrate this tier-1 carbon footprint calculation algorithm processing 1300, the calculation would be accomplished as represented below. Total CO2 = 120 kg (tractor) + 80 kg (harvester) = 200 kg Total CH4 = 5 kg (tractor) + 3 kg (harvester) = 8 kg Total N2O = 1 kg (tractor) + 0.5 kg (harvester) = 1.5 kg

[0130] The CO2-equivalents for each gas 1325 would be calculated as represented below. CO2-Equiv from CO2 = 200 kg * GWP_CO2 = 200 kg CO2-Equiv from CH4 = 8 kg * GWP_CH4 = 200 kg CO2-Equiv from N2O = 1.5 kg * GWP_N2O = 447 kg

[0131] Finally, the total tier-1 carbon footprint would then be the sum of these equivalents as represented below.PCT Patent Application Attorney Docket Number: 47004-244178 Total Tier-1 Footprint = 200 kg (CO2) + 200 kg (CH4) + 447 kg (N2O) = 847 kg CO2-equivalents

[0132] Thus, the total tier-1 carbon footprint would be known for any reported sensor data and may be further reported to either the a user via the graphical user interface, sent to the remote databases in the cloud network 145 for additional processing, retained locally at the edge computing system / access point 130, or potentially used to perform some particular action within the monitored agricultural environment 105 or with the object associated with any of the received and processed sensor data reaching this conclusion.

[0133] Figure 14 illustrates a tier-2 carbon footprint calculation algorithm 1400 of executable code that can be implemented at the edge computing system / access point 130. Execution of the calculation algorithm 1400 may or may not occur precisely at the edge computing system / access point 130 and may involve feedback with the remote databases in the cloud network 145. Of course, it should be understood that the calculation algorithm 1400 algorithm may be stored and accessed from other locations within the network communications system 110 and further executed at a different location than the edge computing system / access point 130. The following presents an example scenario where the tier-2 carbon footprint calculation algorithm 1400 may be utilized and executed by the edge computing system / access point 130.

[0134] As representative of its use within the system 100, suppose there exists a monitored agricultural environment 105 where various energy-consuming equipment is used, such as electric irrigation pumps. These pumps consume electricity, which results in carbon emissions, albeit indirectly, through the power generation process.PCT Patent Application Attorney Docket Number: 47004-244178 The emissions depend on the type of energy source used for generating the electricity. It may be assumed the following data collected 1415 over a specific period for the purposes of understanding the application and use of the tier-2 carbon footprint calculation algorithm 1400. Electricity Consumption by Irrigation Pump 1: 500 kWh Electricity Consumption by Irrigation Pump 2: 300 kWh

[0135] Global Warming Potential (GWP) factors for the emissions resulting from electricity generation can vary based on the energy source. The Global Warming Potential (GWP) factors for the emissions resulting from electricity generation may be provided as cloud-based updates 1440 and 1445 regarding any appropriate changes to such values. These updates would be periodically communicated by the remote databases in the cloud network 145 and received at the edge computing system / access point 130 to update 1440 the tier-2 carbon footprint calculation algorithm 1400. For simplicity, it can be assumed that the GWP factor for electricity- generated emissions is represented below. GWP_Electricity = 0.7 kg CO2-equivalents per kWh (A hypothetical value and can vary based on the actual energy source)

[0136] Having now obtained both recorded sensor values and the values needed regarding the Global Warming Potential (GWP) factors 1440, the tier-2 carbon footprint calculation process may commence in the following manner. First, the tier-2 carbon footprint calculation algorithm 1400 will calculate the total energy consumption 1435 by summing up the kWh used by all equipment. Second, the tier- 2 carbon footprint calculation algorithm 1400 will apply the GWP factor for electricity to convert the energy consumption into CO2-equivalents 1450. To further illustratePCT Patent Application Attorney Docket Number: 47004-244178 this tier-2 carbon footprint calculation algorithm processing, the calculation would be accomplished as represented below: Total Energy Consumption = 500 kWh (Pump 1) + 300 kWh (Pump 2) = 800 kWh

[0137] The CO2-equivalents 1450 for the energy consumption would be calculated as represented below. CO2-Equiv from Electricity = 800 kWh * GWP_Electricity = 560 kg CO2- equivalents

[0138] As illustrated, the total tier-2 carbon footprint for this specific period is represented below. Total Tier-2 Footprint = 560 kg CO2-equivalents

[0139] Thus, the total tier-2 carbon footprint would be known for any reported sensor data and may be further reported to either the user via the graphical user interface, sent to the remote databases in the cloud network 145 for additional processing, retained locally at the edge computing system / access point 130, or potentially used to perform some particular action within the monitored agricultural environment 105 or with the object associated with any of the received and processed sensor data reaching this conclusion.

[0140] Figure 15 illustrates a tier-3 carbon footprint calculation algorithm 1500 of executable code that can be implemented at the edge computing system / access point 130. Execution of the calculation algorithm 1500 may or may not occur precisely at the edge computing system / access point 130 and may involve feedback with the remote databases in the cloud network 145. Of course, it should be understood that the calculation algorithm 1500 algorithm may be stored andPCT Patent Application Attorney Docket Number: 47004-244178 accessed from other locations within the network communications system 110 and further executed at a different location than the edge computing system / access point 130.

[0141] Figure 15 explains the estimation of indirect emissions beyond tier 2, such as transportation and waste management. This algorithm 1500 demonstrates the methodology for collecting data on indirect activities, applying emission factors, and aggregating the results to compute the total tier-3 footprint. The following presents an example scenario where the tier-3 carbon footprint calculation algorithm 1500 may be utilized and executed by the edge computing system / access point 130.

[0142] As representative of its use within the system 100, suppose a monitored agricultural environment 105 engages in various activities contributing to indirect emissions. These activities might include transporting crops to the market and managing farm waste. These specific activities may be relevant to calculating the tier-3 carbon footprint and thus a detailed look is required at their associated data. It may be assumed the following data was collected over a specific period for the purposes of understanding the application and use of the tier-3 carbon footprint calculation algorithm 1500. Transportation of Crops: Distance traveled by truck to market: 100 kilometers Fuel consumption rate of truck: 0.2 liters per kilometer Emission factor for diesel fuel: 2.68 kg CO2-equivalents per liter Waste Management: Amount of organic waste generated: 500 kilograms Emission factor for organic waste decomposition: 0.04 kg CO2- equivalents per kilogramPCT Patent Application Attorney Docket Number: 47004-244178

[0143] Implementing the tier-3 carbon footprint calculation algorithm 1500 may involve the following calculations. Transportation Emissions Calculation: Total fuel used = Distance × Fuel consumption rate = 100 km × 0.2 liters / km = 20 liters CO2-Equiv from Transportation = Total fuel used × Emission factor = 20 liters × 2.68 kg / liter = 53.6 kg CO2-equivalents Waste Management Emissions Calculation: CO2-Equiv from Waste Management = Amount of waste × Emission factor = 500 kg × 0.04 kg CO2-equiv / kg = 20 kg CO2-equivalents Aggregate Tier-3 Emissions: Total Tier-3 Emissions = CO2-Equiv from Transportation + CO2- Equiv from Waste Management = 53.6 kg + 20 kg = 73.6 kg CO2- equivalents

[0144] Thus, the total tier-3 carbon footprint would be known for any reported sensor data and may be further reported to either the user via the graphical user interface, sent to the remote databases in the cloud network 145 for additional processing, retained locally at the edge computing system / access point 130, or potentially used to perform some particular action within the monitored agricultural environment 105 or with the object associated with any of the received and processed sensor data reaching this conclusion.

[0145] Generally, the software modules and applications of the internet-of-things communications system 100 monitoring an agricultural environment 105 can be implemented either at the edge computing system / access point 130 or at the remote databases in the cloud network 145. As the above software applications and algorithms were envisioned to be processed at the edge computing system / access point 130, the following disclosure will illustrate potential software applications and algorithms that may be processed via the remote databases in the cloud networkPCT Patent Application Attorney Docket Number: 47004-244178 145. Of course, there may be, and it is envisioned, that other locations within the system 100 can perform some or all the following software application processing and computational tasks.

[0146] The internet-of-things communications system 100 monitoring an agricultural environment 105 leverages cloud computing resources as a cloud network 145 to help process data received and used by the system 100. The remote databases in the cloud network 145 may include offerings from providers like AWS, Azure, Google Cloud, or any other type of cloud architectural offering. In the remote databases in the cloud network 145, machine learning algorithms, including Random Forests, LSTM, neural networks, generative AI, large language models, or the like, may be deployed to comprehensively analyze collected data. These algorithms analyze data patterns, mobility, and various parameters related to agricultural activities to enhance the accuracy of carbon footprint predictions for a monitored agricultural environment 105. This cloud-based infrastructure ensures scalability and robustness for extensive data analysis that can be done and communicated back to the edge computing system / access point 130 or users of the internet-of-things communications system 100 monitoring an agricultural environment 105.

[0147] Figure 16 illustrates a dataset development process 1600 that can be executed by software applications of the software system 148 and resident within the remote databases of the cloud network 145. Of course, it should be understood that this dataset development process 1600 may be compiled and calculated at other locations potentially within the system’s network communication system 110 and further executed at a different location than associated cloud architecture.PCT Patent Application Attorney Docket Number: 47004-244178

[0148] The dataset development process 1600 may involve aggregating and preprocessing data from various sources 1605, including sensors, GPS, and other internet-of-things devices. These data inputs 1610 may or may not be information related to specifically received data obtained by the system 100 implemented at the monitored agricultural environment location. The raw data undergoes filtering, normalization, and error checking to ensure its reliability and relevance 1615 to the needs and requests of the internet-of-things communications system 100. Once processed, the dataset is structured into a clean dataset 1615, ready for further analysis or input into artificial intelligence or machine learning (AI / ML) models. This systematic approach to dataset development is recommended for ensuring the accuracy and usability of the data in subsequent analytical processes that may later be applicable to the monitored agricultural environment 105 where the system 100 is located.

[0149] Figure 17 illustrates a possible artificial intelligence or machine learning (AI / ML) training process 1700 that can be executed by software applications of the software system 148 and resident within the remote databases of the cloud network 145. Of course, it should be understood that this artificial intelligence or machine learning (AI / ML) training process 1700 may be accomplished at other locations potentially within the system’s network communication system 110 and further executed at a different location than associated cloud architecture.

[0150] The artificial intelligence or machine learning (AI / ML) training process 1700 begins with the developed dataset, which is used to train machine learning models. This involves selecting appropriate algorithms 1705, feeding them with the preprocessed data 1710, and iteratively refining the models through training cyclesPCT Patent Application Attorney Docket Number: 47004-244178 1715. The trained models are then evaluated for accuracy and performance. Upon successful evaluation 1720, these models are ready to be deployed for real-time data analysis or predictive tasks within the internet-of-things communications system 100 monitoring an agricultural environment 105. These trained artificial intelligence or machine learning (AI / ML) models can be used to further analyze 1725 and interpretation of data representing a specific monitored agricultural environment where the internet-of-things communications system 100 is deployed.

[0151] Figure 18 illustrates a possible generation process 1800 to determine and output useful or requested analysis via the trained artificial intelligence or machine learning (AI / ML) model used by the internet-of-things communications system 100 to better understand and act within the monitored environment 105. Of course, it should be understood that this artificial intelligence or machine learning (AI / ML) generation process 1800 may be accomplished at other locations potentially within the system’s network communication system 110 and further executed at a different location than associated cloud architecture.

[0152] The Figure 18 flowchart outlines how the internet-of-things communications system 100 monitoring an agricultural environment 105 may leverage and use artificial intelligence or machine learning (AI / ML) models to generate actionable recommendations from processed data. After data collection 1805 and preprocessing is done by the edge computing system / access point 130, the preprocessed data may be sent to the cloud for comprehensive analysis 1810. Here, artificial intelligence or machine learning (AI / ML) models may be called or requested to perform a particular action 1815. These artificial intelligence or machine learning (AI / ML) models can be trained to accommodate and provide the necessary outputPCT Patent Application Attorney Docket Number: 47004-244178 required from the called or requested action. For example, the artificial intelligence or machine learning (AI / ML) models may analyze the preprocessed data, identifying patterns 1810 and insights relevant to agricultural practices that may be occurring or may occur in the future 1820 at the monitored agricultural environment 105. Based on this analysis, the artificial intelligence or machine learning (AI / ML) models may generate tailored recommendations 1825 that are possible to be implemented by the internet-of-things communications system 100 monitoring an agricultural environment 105. These generated recommendations, tasks, or actions can then be conveyed back to the user through the graphical user interface associated with the user’s access to the system. If is further envisioned that these generated recommendations, tasks, or actions can then be conveyed 1830 back to the edge computing system / access point 130 and end users to be reviewed via the graphical user interface. These generated recommendations, tasks, or actions can suggest where a particular action may be taken to address and implement a generated recommendations, tasks, or actions system wide, with a specific sensor or subsets of sensors, or even upon an object from which a particular sensor receives data. This process enables farmers and users the ability to receive data-driven guidance for optimizing their farming strategies and monitor the health and compliance of their locally monitored agricultural environment 105.

[0153] Figure 19 illustrates a possible delivery process 1900 related to the training of artificial intelligence or machine learning (AI / ML) models and a subsequent deployment to edge computing system / access point 130 for implementation of action. This delivery process of Figure 19 focuses on the training of artificial intelligence or machine learning (AI / ML) models and their subsequent deploymentPCT Patent Application Attorney Docket Number: 47004-244178 within the system 100 for which the generated recommendation, action, or task may be relevant. Initially, the artificial intelligence or machine learning (AI / ML) models are trained 1910 in the remote databases of the cloud network 145 using extensive datasets 1905. However, once these artificial intelligence or machine learning (AI / ML) models are trained 1910, these artificial intelligence or machine learning (AI / ML) models may be evaluated 1915, optimized and finalized 1920. From there, these artificial intelligence or machine learning (AI / ML) models are packaged 1925, transmitted, and stored 1930 at the edge computing system / access point 130. At the edge computing system / access point 130, these artificial intelligence or machine learning (AI / ML) models may be further deployed for real-time data processing and analysis without need of the remote databases in the cloud network 145 or use of the cloud architecture. This possible delivery process ensures that an edge computing system / access point 130 is equipped with the latest artificial intelligence or machine learning (AI / ML) capabilities to further enable efficient on-site data processing and decision-making support for users at the local level.

[0154] The system 100 as an internet-of-things communications network deployed within an agricultural environment 105 integrates low-power wireless networks, edge computing, and cloud analytics to enable end-to-end carbon emission monitoring in agricultural environments. The following are examples of technology useable to create and offer components of the system 100. One example set up of technology used to create components at the device-level implementation may use the Newracom NRF7292 chipset running a custom-built `sample_ioct_client` application. This application collects real-time data from sensors measuring Tier 1, Tier 2, and Tier 3 greenhouse gas (GHG) emissions, such as CO2, CH4, and N2O, andPCT Patent Application Attorney Docket Number: 47004-244178 transmits them over a Wi-Fi HaLow (IEEE 802.11ah) link to the edge computing system / access point 130. At the edge computing system / access point 130, the edge computing system / access point 130 processes incoming data and calculates CO2- equivalent (CO2e) values using Tier 1 (direct emissions), Tier 2 (indirect emissions), and Tier 3 (supply chain emissions) values. The edge computing system / access point 130 performs filtering, anomaly detection, visualization, and historical trend comparison using a lightweight Flask server and MQTT-based communication. While current data is simulated, the edge computing system / access point 130 is fully capable of working with real sensor inputs when available, as the ingestion logic is designed to switch seamlessly to live data collection.

[0155] At the remote databases in the cloud network 145, the Flask-based application receives processed emissions data, stores it in a time-series database, and generates dynamic visualizations and daily recommendations. Cloud analytics include hourly and daily CO2e trends and tier-specific gas trends, which are fed back to edge devices via MQTT. The internet-of-things communications system 100 simulates a real-time feedback loop for emission monitoring, offering suggestions such as reducing tractor use, optimizing nitrogen application, or improving livestock practices. Figure 20 illustrates an example graphical user interface screenshot viewable on a display of the edge computing system / access point 130 by users such as farmers or the admin at the network communications system 110. Figure 21 illustrates a second example graphical user interface screenshot viewable on a display of the edge computing system / access point 130 by users such as farmers or the admin at the network communications system 110.PCT Patent Application Attorney Docket Number: 47004-244178

[0156] Figure 22 illustrates an example graphical user interface screenshot viewable on a dashboard display of the remote databases in the cloud network 145 or accessible by users connecting through the cloud network interface. The cloud dashboard supports geospatial tagging and personalized messages for users, making the system 100 and its graphical user interface platform a robust tool for precision environmental monitoring and climate-smart decision-making. Overall, implementation demonstrates the complete pipeline of the system 100 in use from real-time sensing at the field environment 105 to actionable insights at the remote databases in the cloud network 145, validating its readiness for deployment in agriculture or other emission-critical domains.

[0157] The following are examples of technology useable to create and evaluate use of the network communications system 110 and the 1-hop Wi-Fi Halow (Station to AP) network communications that occur within system 100. Performance evaluation of Wi-Fi HaLow (IEEE^802.11ah) can be done using two Alfa Network AHPI-7292S devices upgraded to a w wireless interface like OpenWrt: one serving as a gateway (AP + edge computing on a Raspberry^Pi as the edge computing system / access point 130) and the other as a station (STA or sensor / station 120). Both units communicate on sub-1^GHz channels (1^MHz or 2^MHz), typically at or below 14^dBm for regulatory compliance, with throughput and latency measured via TCP iPerf and ping, respectively. The AP or edge computing system / access point 130 can be placed in a middle area and the STA or sensor / station 120 can be moved to various points. Then, communications occurring between the units can capture the average round-trip times (RTT) in milliseconds and transport-layer throughput in megabits per second (Mbps). Configuration details—like channel, MCSPCT Patent Application Attorney Docket Number: 47004-244178 (modulation / coding level), and bandwidth—may be managed through the wireless interface.

[0158] Figure^23 illustrates the resulting throughput measurements across Modulation and Coding Scheme (MCS) indices, beginning with MCS^10 (lowest data rate) and extending through MCS^5 (higher data rate) recorded using the example technology units. The two bandwidth options—1^MHz and 2^MHz—are compared under two overhead conditions (“RTS / CTS + Data + ACK” versus “Data + ACK” alone). This demonstrates how reducing control overhead or increasing channel width yields higher net throughput. These results align well with the envisioned use of the system 100 of an internet-of-things communications network deployed within an agricultural environment 105 as the system 100 emphasizes robust low-power connectivity in agricultural environments for real-time, location-specific emission monitoring. By adopting either 1^MHz or 2^MHz sub-1^GHz channels, the field nodes can reliably report Tier^1, Tier^2, and Tier^3 carbon data (e.g., direct, indirect, and supply-chain emissions) to an edge computing system / access point 130 gateway. The higher throughput of 2^MHz can accelerate data collection in moderate-range deployments, while 1^MHz may suffice for extremely long-range or particularly obstructed scenarios. Overall, this example set up confirms that 802.11ah-based solutions, as disclosed in above and throughout this application, can effectively integrate both bandwidth settings to optimize emissions monitoring and sustainable farming practices.

[0159] Further, as illustrated in Figure 24, channel 1^MHz and the added overhead of RTS / CTS generally increase round-trip times compared to 2^MHz with Data + ACK alone. As MCS improves from left to right (i.e., from MCS^10 to higher rates), thePCT Patent Application Attorney Docket Number: 47004-244178 protocol can transmit packets more efficiently, thus reducing average latency overall. The 2^MHz (Data + ACK) remain lowest across MCS levels, indicating that less control overhead and a wider channel yield quicker turnaround. Conversely, 1^MHz (RTS / CTS + Data + ACK) sits highest, reflecting the accumulated overhead of handshaking mechanisms and narrower bandwidth.

[0160] This flexibility in adjusting MCS and channel bandwidth suits the varied demands of a heterogeneous system 100 of an internet-of-things communications network deployed within an agricultural environment 105 wherein remote Tier^1, Tier^2, or Tier^3 emissions data may be captured under different connectivity constraints. Through the proposed Wi-Fi^HaLow solution, edge-based networks can dynamically balance extended range, low power, and adequate throughput / latency for precise carbon monitoring tasks.

[0161] The embodiments were chosen and described in order to best explain the principles of the invention and its practical application to thereby enable others skilled in the art to best utilize the invention in various embodiments and with various modifications as are suited to the particular use contemplated.

[0162] As various modifications could be made in the construction and method herein described and illustrated without departing from the scope of the invention, it is intended that all matter contained in the foregoing description or shown in the accompanying drawings shall be interpreted as illustrative rather than limiting. For example, the overall configuration of the internet-of-things communications network deployed within an agricultural environment system, the plurality of devices used within, software applications executable thereon, and the design and configuration of potential networking communication protocols or node locations may be employedPCT Patent Application Attorney Docket Number: 47004-244178 but can achieve the same functionality of the underlying invention. Thus, the breadth and scope of the present invention should not be limited by any of the above- described example embodiments but should be defined only in accordance with the following claims appended hereto and their equivalents.

Claims

PCT Patent Application Attorney Docket Number: 47004-244178 What is claimed is:

1. A system for data collection and data analysis for use within an environment, the system comprising: at least one device having a device network interface, the at least one device being able to receive a data input associated with an object monitored by the at least one device; an access point, the access point having an access point memory, an access point network interface, and an access point processor usable in cooperation with the access point memory; a remote database, the remote database having a remote database memory, a remote database network interface, and a remote database processor usable in cooperation with the remote database memory; a communications network including the at least one device, the access point, and the remote database, the communications network handling transmission and reception of a signal representing the data input with each at least one device, the access point, and the remote database; a data analysis module, the data analysis module structured, stored, and executed by either the access point processor usable in cooperation with the access point memory or the remote database processor usable in cooperation with the remote database memory, the data analysis module containing a plurality of instructions configure to: preprocess the data input associated with the object monitored by the at least one device when the signal representing the data input is received byPCT Patent Application Attorney Docket Number: 47004-244178 either the access point or the remote database via the communications network; calculate an attribute associated with the preprocessed data input; associate the attribute with the object from which the data input was received; and transmit an output with the data input attribute.

2. The system for data collection and data analysis for use within the environment of claim 1, wherein the environment is an agricultural environment.

3. The system for data collection and data analysis for use within the environment of any of claims 1-2, wherein the monitored object is an agricultural object, the agricultural object executing an agricultural function within the environment.

4. The system for data collection and data analysis for use within the environment of any of claims 1-3, wherein at least one device is a plurality of devices.

5. The system for data collection and data analysis for use within the environment of any of claims 1-4, wherein the device interface is a device transceiver, the device transceiver able to transmit the signal wirelessly onto the communications network.

6. The system for data collection and data analysis for use within the environment of any of claims 1-5, wherein the device transceiver communicates the signal onto the communications network via a Wi-Fi HaLow communications protocol, thePCT Patent Application Attorney Docket Number: 47004-244178 Wi-Fi HaLow communications protocol being a modified Wi-Fi HaLow communications protocol.

7. The system for data collection and data analysis for use within the environment of any of claims 1-6, wherein the at least one device includes operates with a power source.

8. The system for data collection and data analysis for use within the environment of any of claims 1-7, wherein the at least one device includes a device processor, the device processor being a microprocessor capable of executing instructions designated to be performed by the at least one device.

9. The system for data collection and data analysis for use within the environment of any of claims 1-8, wherein the at least one device includes a device memory, the device processor usable in cooperation with the device memory to execute instructions stored within the device memory and to be performed by the at least one device.

10. The system for data collection and data analysis for use within the environment of any of claims 1-9, wherein instructions of the data analysis module, or a portion of the data analysis module, may be stored within the device memory and executed by the device processor upon the data input received by the at least one device and associated with the monitored object.

11. The system for data collection and data analysis for use within the environment of any of claims 1-10, wherein instructions of a communications optimization module, or a portion of the communications optimization module, may be stored within the device memory and executed by the device processor for aPCT Patent Application Attorney Docket Number: 47004-244178 determination related to the signal representing the data input received by the at least one device.

12. The system for data collection and data analysis for use within the environment of any of claims 1-11, wherein the at least one device includes an analog to digital converter, the analog to digital converter transforming an analog data input into a digital signal representing the analog data input received by the at least one device.

13. The system for data collection and data analysis for use within the environment of any of claims 1-12, wherein the at least one device is a sensor, the sensor able to receive the data input associated with the monitored object and transmit the signal via the communications network.

14. The system for data collection and data analysis for use within the environment of any of claims 1-13, wherein the at least one device is a global positioning system unit, the sensor able to receive the data input associated with the monitored object and transmit the signal via the communications network.

15. The system for data collection and data analysis for use within the environment of any of claims 1-14, wherein the global positioning system unit transmits the signal via a second communications network.

16. The system for data collection and data analysis for use within the environment of any of claims 1-15, wherein the at least one device of the plurality of devices is a relay, the relay able to send and receive a plurality of signals upon the communications network including the signal representing the data input received by the at least one device.PCT Patent Application Attorney Docket Number: 47004-244178 17. The system for data collection and data analysis for use within the environment of claim 16, wherein the device interface is a relay transceiver, the relay transceiver is able to wirelessly transmit and send the plurality of signals upon the communications network including the signal representing the data input received by the at least one device.

18. The system for data collection and data analysis for use within the environment of any of claims 16-17, wherein the relay transceiver communicates the signal and the plurality of signals onto the communications network via a Wi-Fi HaLow communications protocol, the Wi-Fi HaLow communications protocol being a modified Wi-Fi HaLow communications protocol.

19. The system for data collection and data analysis for use within the environment of any of claims 16-18, wherein the relay operates with a power source.

20. The system for data collection and data analysis for use within the environment of any of claims 16-19, wherein the relay includes a relay processor, the relay processor being a microprocessor capable of executing instructions designated to be performed by the relay.

21. The system for data collection and data analysis for use within the environment of any of claims 16-20, wherein the relay includes a relay memory, the relay processor usable in cooperation with the relay memory to execute instructions stored within the relay memory and to be performed by the relay.

22. The system for data collection and data analysis for use within the environment of any of claims 16-21, wherein instructions of the data analysis module, or a portion of the data analysis module, may be stored within the relay memory andPCT Patent Application Attorney Docket Number: 47004-244178 executed by the relay processor upon the plurality of signals including the signal representing the data input received by the at least one device.

23. The system for data collection and data analysis for use within the environment of any of claims 1-22, wherein the access point is able to send and receive a plurality of signals upon the communications network including the signal representing the data input received by the at least one device, the access point being configure to communication with all devices upon the communications network including relays and devices as well as communicate with the remote database.

24. The system for data collection and data analysis for use within the environment of any of claims 1-23, wherein the access point interface is a plurality of access point interfaces.

25. The system for data collection and data analysis for use within the environment of any of claims 1-24, wherein all the access point interfaces of the plurality of access point interfaces are access point transceivers, the access point transceivers able to wirelessly transmit and send the plurality of signals upon the communications network and with the remote database.

26. The system for data collection and data analysis for use within the environment of any of claims 1-25, wherein a second point interface of the plurality of access point interfaces is a second access point transceiver, the second access point transceiver able to wirelessly transmit and send the plurality of signals including the signal representing the data input received by the at least one device to the remote database.PCT Patent Application Attorney Docket Number: 47004-244178 27. The system for data collection and data analysis for use within the environment of claim 26, wherein the second access point transceiver wirelessly transmits and receives the plurality of signals including the signal representing the data input received by the at least one device to the remote database on a second communications network.

28. The system for data collection and data analysis for use within the environment of claim 27, wherein the second communications network is different from the first communications network.

29. The system for data collection and data analysis for use within the environment of claim 28, wherein the second communications network is a cellular communications network.

30. The system for data collection and data analysis for use within the environment of any of claims 1-29, wherein the plurality of access point transceivers communicate the signal and the plurality of signals onto the communications network or to the remote database via a Wi-Fi HaLow communications protocol, the Wi-Fi HaLow communications protocol being a modified Wi-Fi HaLow communications protocol.

31. The system for data collection and data analysis for use within the environment of any of claims 1-30, wherein the access point operates with a power source.

32. The system for data collection and data analysis for use within the environment of any of claims 1-31, wherein the access point processor is an access point microprocessor capable of executing instructions designated to be performed by the access point.PCT Patent Application Attorney Docket Number: 47004-244178 33. The system for data collection and data analysis for use within the environment of any of claims 1-32, wherein the access point processor instructs the transmission of access point information and is in communication with the plurality of access point transceivers.

34. The system for data collection and data analysis for use within the environment of any of claims 1-33, wherein instructions of the data analysis module, or a portion of the data analysis module, may be stored within the access point memory and executed by the access point processor upon the plurality of signals including the signal representing the data input received by the at least one device.

35. The system for data collection and data analysis for use within the environment of any of claims 1-34, wherein instructions of the data analysis module, or a portion of the data analysis module, may be stored within the access point memory and executed by the access point processor upon a plurality of remote database signals received by the access point.

36. The system for data collection and data analysis for use within the environment of any of claims 1-35, wherein instructions of a communications optimization module, or a portion of the communications optimization module, may be stored within the access point memory and executed by the access point processor for a determination related to the plurality of signals including the signal representing the data input received by the at least one device.

37. The system for data collection and data analysis for use within the environment of any of claims 1-34, wherein the access point is an edge computing system.PCT Patent Application Attorney Docket Number: 47004-244178 38. The system for data collection and data analysis for use within the environment of any of claims 1-37, wherein the access point includes a graphical user interface to display information related to the system to an end user.

39. The system for data collection and data analysis for use within the environment of any of claims 1-38, wherein the access point includes a user input interface to receive information related to the system by an end user.

40. The system for data collection and data analysis for use within the environment of any of claims 1-39, wherein the communications network involves communication between a plurality of devices including the at least one device and the access point.

41. The system for data collection and data analysis for use within the environment of any of claims 1-40, wherein the communications network involves communication between a plurality of devices including the at least one device, the access point, and the remote database.

42. The system for data collection and data analysis for use within the environment of any of claims 1-41, wherein the communications network involves a pathway for communicating between a plurality of devices via a plurality of signals representing data input received by the plurality of devices, the pathway originating form at least one device and ending at the access point; and the access point communicating the plurality of signals as needed to the remote database.

43. The system for data collection and data analysis for use within the environment of any of claims 1-42, wherein select devices of the communications network mayPCT Patent Application Attorney Docket Number: 47004-244178 communicate a device specific signal directly to the remote database without use of the communications network.

44. The system for data collection and data analysis for use within the environment of any of claims 1-43, wherein the communications network is a mesh network architecture.

45. The system for data collection and data analysis for use within the environment of any of claims 1-44, wherein the mesh network architecture of the communications network involves a plurality of pathways for communicating between a plurality of devices via a plurality of signals representing data input received by the plurality of devices, the plurality of pathways originating from at least one device of the plurality of devices and ending at the access point.

46. The system for data collection and data analysis for use within the environment of any of claims 1-45, wherein the mesh network architecture of the communications network involves a configuration as viewed within Figure 5 and discussed within the application.

47. The system for data collection and data analysis for use within the environment of any of claims 1-46, wherein the mesh network architecture of the communications network involves a configuration as viewed within Figure 6 and discussed within the application.

48. The system for data collection and data analysis for use within the environment of any of claims 1-47, wherein the communications network transmits signals via a Wi-Fi HaLow communications protocol, the Wi-Fi HaLow communications protocol being a modified Wi-Fi HaLow communications protocol.PCT Patent Application Attorney Docket Number: 47004-244178 49. The system for data collection and data analysis for use within the environment of any of claims 1-48, wherein the modified Wi-Fi HaLow communications protocol employs a driver configured the modified Wi-Fi HaLow communications protocol within a memory of each of the plurality of devices or access points present within the communications network.

50. The system for data collection and data analysis for use within the environment of any of claims 1-49, wherein the modified Wi-Fi HaLow communications protocol alters a layer of the communication protocol stack in of the modified Wi-Fi HaLow communications protocol.

51. The system for data collection and data analysis for use within the environment of any of claims 1-50, wherein a communications optimization module may be employed within the communications network.

52. The system for data collection and data analysis for use within the environment of any of claims 1-51, wherein instructions of a communications optimization module, or a portion of the communications optimization module, may be stored within the access point memory, the device memory, the relay memory, the remote server memory, or a memory of any of the plurality of devices connected to the communications network, the communications optimization module or portion thereof further executed by the associated processor of the device for a determination related to the plurality of signals moving on the communications network.

53. The system for data collection and data analysis for use within the environment of any of claims 1-52, wherein instructions of a communications optimization module, or a portion of the communications optimization module, may be storedPCT Patent Application Attorney Docket Number: 47004-244178 within an access point memory or a relay memory connected to the communications network, the communications optimization module executed by the associated access point memory or relay processor for a determination related to the plurality of signals moving on the communications network.

54. The system for data collection and data analysis for use within the environment of any of claims 1-53, wherein a communications optimization module optimizes a pathway for communications occurring upon the communications network.

55. The system for data collection and data analysis for use within the environment of any of claims 1-54, wherein the communications optimization module includes a series of groupings to be made with all of the plurality of devices, relays, or access points resident on the communications network.

56. The system for data collection and data analysis for use within the environment of any of claims 1-55, wherein the communications optimization module includes a determination of network traffic used by each group of the series of groupings transmitting information on the communications network.

57. The system for data collection and data analysis for use within the environment of any of claims 1-56, wherein the communications optimization module includes a determination of a plurality of pathways possible for network traffic transmission by each group of the series of groupings on the communications network.

58. The system for data collection and data analysis for use within the environment of any of claims 1-57, wherein the communications optimization module includes a determination of a plurality of pathways possible for a device of the plurality of devices, relay, or access point to send and receive network traffic on the communications network.PCT Patent Application Attorney Docket Number: 47004-244178 59. The system for data collection and data analysis for use within the environment of any of claims 1-58, wherein the communications optimization module includes a determination altering a communication pathway between a device of the plurality of devices, relay, or access point to send and receive network traffic on the communications network from a first route to a second route.

60. The system for data collection and data analysis for use within the environment of any of claims 1-59, wherein the determination to alter a communication pathway between a device of the plurality of devices, relay, or access point to send and receive network traffic on the communications network from a first route to a second route is done based on a determined amount of network traffic or network traffic threshold of the communications network.

61. The system for data collection and data analysis for use within the environment of any of claims 1-60, wherein the altering of a communication pathway between a device of the plurality of devices, relay, or access point to send and receive network traffic on the communications network from a first route to a second route is done based on a regrouping to the series of groupings assigned to all of the plurality of devices, relays, or access points resident on the communications network.

62. The system for data collection and data analysis for use within the environment of any of claims 1-61, wherein the communications optimization module regroups the series of groupings assigned to all of the plurality of devices, relays, or access points resident on the communications network to address a desired outcome.PCT Patent Application Attorney Docket Number: 47004-244178 63. The system for data collection and data analysis for use within the environment of any of claims 1-62, wherein the communications optimization module assigns each signal of the plurality of signals a priority level for optimization of network communications.

64. The system for data collection and data analysis for use within the environment of any of claims 1-63, wherein the priority level assigned to each signal of the plurality of signals is determined by a characteristic of the data information contained within the signal.

65. The system for data collection and data analysis for use within the environment of any of claims 1-64, wherein the priority level assigned to each signal of the plurality of signals is determined by a characteristic of the data information collected by the at least one device associated with the object.

66. The system for data collection and data analysis for use within the environment of any of claims 1-65, wherein the priority level assigned to each signal of the plurality of signals may be further adjusted and reassigned by the communications optimization module to address network communications on the communications network.

67. The system for data collection and data analysis for use within the environment of any of claims 1-66, wherein the data analysis module may be stored and executed by the remote database or the access point.

68. The system for data collection and data analysis for use within the environment of any of claims 1-67, wherein the data analysis module is separated into a plurality of portions, and wherein a first portion of the data analysis module may be storedPCT Patent Application Attorney Docket Number: 47004-244178 and executed by the access point and the second portion of the data analysis module may be stored and executed by the remote database.

69. The system for data collection and data analysis for use within the environment of any of claims 1-68, wherein the data analysis module processes and executes instructions upon a plurality of signals representing data input received by the plurality of devices, the data input information within the signal associated with an object monitored by each device of the plurality of devices.

70. The system for data collection and data analysis for use within the environment of any of claims 1-69, wherein the data input information within the plurality of signals includes a reading representing an agricultural action of the associated object.

71. The system for data collection and data analysis for use within the environment of any of claims 1-70, wherein the data input information within the plurality of signals includes a reading representing emissions characteristics of an agricultural action of the associated object.

72. The system for data collection and data analysis for use within the environment of any of claims 1-71, wherein the data input information within the plurality of signals includes a reading representing a greenhouse gas related characteristics of an agricultural action of the associated object.

73. The system for data collection and data analysis for use within the environment of any of claims 1-72, wherein the data analysis module processes and executes a preprocessing of the data input information associated with the object on the signal when it is received by the access point.PCT Patent Application Attorney Docket Number: 47004-244178 74. The system for data collection and data analysis for use within the environment of any of claims 1-73, wherein the data analysis module processes and executes a preprocessing of the data input information associated with the object on the signal before it is received by the access point.

75. The system for data collection and data analysis for use within the environment of any of claims 1-74, wherein the data analysis module processes and executes a preprocessing of the data input information associated with the object on the signal when it is received by the remote database.

76. The system for data collection and data analysis for use within the environment of any of claims 1-75, wherein the data analysis module processes and executes a preprocessing of the data input information associated with a plurality of objects within a plurality of signals to create a common data set for further actions by the data analysis module.

77. The system for data collection and data analysis for use within the environment of any of claims 1-76, wherein the data analysis module processes and executes a classification of the data input information associated with a plurality of objects within a plurality of signals, the classification of data input assigns a level indicator to the data input information associated with the plurality of objects within the plurality of signals.

78. The system for data collection and data analysis for use within the environment of any of claims 1-77, wherein the data analysis module assigns a tier to the data input information associated with the plurality of objects within the plurality of signals.PCT Patent Application Attorney Docket Number: 47004-244178 79. The system for data collection and data analysis for use within the environment of any of claims 1-78, wherein the data analysis module processes and executes a first tier algorithm, the first tier algorithm being executed upon a set of data input information assigned by the data analysis module to be representative of a first tier of data input information associated with the plurality of objects within the environment.

80. The system for data collection and data analysis for use within the environment of any of claims 1-79, wherein the data analysis module processes and executes a first-tier algorithm at the access point.

81. The system for data collection and data analysis for use within the environment of claim 80, wherein the data analysis module transmits the first-tier algorithm result from the access point to the remote server.

82. The system for data collection and data analysis for use within the environment of any of claims 80-81, wherein the data analysis module transmits the first-tier algorithm result to a graphical user interface, the graphical user interface accessible by an end user of the system.

83. The system for data collection and data analysis for use within the environment of any of claims 1-78, wherein the data analysis module processes and executes a second tier algorithm, the second tier algorithm being executed upon a set of data input information assigned by the data analysis module to be representative of a second tier of data input information associated with the plurality of objects within the environment.PCT Patent Application Attorney Docket Number: 47004-244178 84. The system for data collection and data analysis for use within the environment of any of claims 1-78 or 83, wherein the data analysis module processes and executes a second-tier algorithm at the access point.

85. The system for data collection and data analysis for use within the environment of claim 84, wherein the data analysis module transmits the second-tier algorithm result from the access point to the remote server.

86. The system for data collection and data analysis for use within the environment of any of claims 84-85, wherein the data analysis module transmits the second-tier algorithm result to a graphical user interface, the graphical user interface accessible by an end user of the system.

87. The system for data collection and data analysis for use within the environment of any of claims 1-78, wherein the data analysis module processes and executes a third tier algorithm, the third tier algorithm being executed upon a set of data input information assigned by the data analysis module to be representative of a third tier of data input information associated with the plurality of objects within the environment.

88. The system for data collection and data analysis for use within the environment of any of claims 1-78 or 87, wherein the data analysis module processes and executes a third-tier algorithm at the access point.

89. The system for data collection and data analysis for use within the environment of claim 88, wherein the data analysis module transmits the third-tier algorithm result from the access point to the remote server.

90. The system for data collection and data analysis for use within the environment of any of claims 88-89, wherein the data analysis module transmits the third-tierPCT Patent Application Attorney Docket Number: 47004-244178 algorithm result to a graphical user interface, the graphical user interface accessible by an end user of the system.

91. The system for data collection and data analysis for use within the environment of any of claims 1-90, wherein the data analysis module is processed and executed by the remote server.

92. The system for data collection and data analysis for use within the environment of any of claims 1-91, wherein the remote server transmits information related to either a first-tier algorithm, a second-tier algorithm, or a third-tier algorithm, for use by the data analysis module functionality performed by the access point.

93. The system for data collection and data analysis for use within the environment of any of claims 1-92, wherein the data analysis module is separated into a plurality of portions, and wherein a first portion of the data analysis module may be stored and executed by the access point and the second portion of the data analysis module may be stored and executed by the remote database, the second portion of the data analysis module being processed after the first portion of the data analysis module is processed.

94. The system for data collection and data analysis for use within the environment of any of claims 1-93, wherein the data analysis module includes use of a machine learning data set.

95. The system for data collection and data analysis for use within the environment of any of claims 1-94, wherein the machine learning data set is aggregated and determined by processing on the remote database.

96. The system for data collection and data analysis for use within the environment of any of claims 1-95, wherein the machine learning data set contains bothPCT Patent Application Attorney Docket Number: 47004-244178 information received and transmitted through the system and information representative of outside systems.

97. The system for data collection and data analysis for use within the environment of any of claims 1-96, wherein the data analysis module includes training of a machine learning model.

98. The system for data collection and data analysis for use within the environment of any of claims 1-97, wherein the machine learning model is defined and created by the machine learning data set, the machine learning model being applicable to an environmental characteristic monitored by the system within the environment.

99. The system for data collection and data analysis for use within the environment of any of claims 1-98, wherein the machine learning model is focused on an emissions characteristic monitored by the system within the environment.

100. The system for data collection and data analysis for use within the environment of any of claims 1-99, wherein the machine learning model is focused on a greenhouse gas emissions characteristic monitored by the system within the environment.

101. The system for data collection and data analysis for use within the environment of any of claims 1-100, wherein the data analysis module creates a plurality of machine learning models, each machine learning model focused on a subset of information related to the environmental characteristic monitored by the system within the environment.

102. The system for data collection and data analysis for use within the environment of any of claims 1-101, wherein the data analysis module implements at least one of the plurality of machine learning models to analyzePCT Patent Application Attorney Docket Number: 47004-244178 information received and processed by the system related to the environmental characteristic monitored within the environment.

103. The system for data collection and data analysis for use within the environment of any of claims 1-102, wherein the data analysis module outputs at least one recommendation or insight from implementing at least one of the plurality of machine learning models to analyze information received and processed by the system related to the environmental characteristic monitored within the environment.

104. The system for data collection and data analysis for use within the environment of any of claims 1-103, wherein the data analysis module outputs at least one recommendation or insight to a graphical user interface accessible by the end user of the system.

105. The system for data collection and data analysis for use within the environment of any of claims 1-104, wherein the data analysis module repackages at least one of the plurality of machine learning models to analyze information received and processed by the system.

106. The system for data collection and data analysis for use within the environment of any of claims 1-105, wherein the remote database transmits at least one of the repackaged plurality of machine learning models to the access point.

107. The system for data collection and data analysis for use within the environment of any of claims 1-106, wherein the access point stores and executes at least one of the repackaged plurality of machine learning models atPCT Patent Application Attorney Docket Number: 47004-244178 the access point upon data from the plurality of signals received by the access point related to an environmental characteristic monitored by the system.

108. The system for data collection and data analysis for use within the environment of any of claims 1-107, wherein the access point outside any insight or recommendation from processing the at least one of the repackaged plurality of machine learning models at the access point to either a graphical user interface accessible by the end user of the system or the remote database.

109. A system for data collection and data analysis for use within an environment, the system comprising: at least one device having a device network interface, the at least one device being able to receive a data input associated with an object monitored by the at least one device; an access point, the access point having an access point memory, an access point network interface, and an access point processor usable in cooperation with the access point memory; a remote database, the remote database having a remote database memory, a remote database network interface, and a remote database processor usable in cooperation with the remote database memory; and a communications network including the at least one device, the access point, and the remote database, the communications network handling transmission and reception of a signal representing the data input with each at least one device, the access point, and the remote database.

110. A system for data collection and data analysis for use within an environment, the system comprising:PCT Patent Application Attorney Docket Number: 47004-244178 at least one device having a device network interface, the at least one device being able to receive a data input associated with an object monitored by the at least one device; an access point, the access point having an access point memory, an access point network interface, and an access point processor usable in cooperation with the access point memory; a remote database, the remote database having a remote database memory, a remote database network interface, and a remote database processor usable in cooperation with the remote database memory; and a communications network including the at least one device, the access point, and the remote database, the communications network handling transmission and reception of a signal representing the data input with each at least one device, the access point, and the remote database, the data analysis module containing a plurality of instructions configure to: preprocess the data input associated with the object monitored by the at least one device when the signal representing the data input is received by either the access point or the remote database via the communications network.

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