478 results about "Mobile apps" patented technology

An AI-powered agile project management system for automatic risk assessment and mitigation, including: a risk identification module configured to extract project data from agile project management tools, including but not limited to Jira, Trello, Asana, and Monday.com, and identify potential risks using machine learning and NLP; a risk analysis module configured to assign risk scores based on probability, impact, and severity using predictive analytics, where the module uses historical data, real-time project status, and external dependencies to determine the severity and impact of risks; a real-time monitoring module configured to continuously track project conditions, detect anomalies, and generate immediate notifications via email, mobile apps, or messaging platforms when high-risk events are identified; a risk mitigation module configured to dynamically recommend and execute proactive corrective actions such as task reassignment, resource optimization, schedule adjustments, and implementation of alternative strategies using AI-driven decision-making, where the actions can be automated through predefined workflows or manually adjusted based on AI recommendations; an AI-driven task prioritization module configured to dynamically prioritize tasks based on risk factors, project deadlines, and team workload distribution; an integration module configured to ensure seamless compatibility with existing Agile project management frameworks through API-based synchronization; a learning and continuous improvement module configured to refine risk prediction models over time using machine learning and historical risk mitigation results, with AI-driven models continuously updating risk assessment mechanisms based on evolving project conditions, industry-specific risk factors, and historical performance metrics; a compliance and audit reporting module configured to automatically generate risk reports, audit logs, and compliance checklists; a customizable risk assessment configuration module configured to allow project managers to define custom risk parameters, probability thresholds, and mitigation preferences; an interactive dashboard module configured to visualize data in real time, including risk trends, effectiveness of remedial actions, and analysis of project progress; and a scalability feature configured to be used in industries such as IT, healthcare, finance, construction, and manufacturing.

A machine learning-based fraud detection system (100) for financial transactions, comprising the following: a data collection and preprocessing module configured to capture transaction data from financial institutions, payment gateways and bank modules, and to perform data cleansing, normalization and format conversion; a module for creating user profiles and behavioral analyses, configured to create dynamic user profiles based on historical transaction patterns, spending habits, device usage, and geographic location; an anomaly detection and risk assessment module configured to use machine learning algorithms to detect deviations from normal transaction patterns and assign a dynamic risk rating to each transaction; a fraud detection module configured to classify transactions as legitimate or fraudulent based on supervised and unsupervised learning techniques, including decision trees, support vector machines (SVMs), and deep learning models; a rule-based and hybrid fraud detection module configured to integrate predefined rule-based fraud detection mechanisms with AI-driven anomaly detection to improve fraud detection accuracy; a real-time fraud detection and warning module configured to monitor transactions in real time and generate security alerts via SMS, email or mobile app when suspicious activity is detected; a transaction verification and multi-factor authentication (MFA) module configured to implement adaptive authentication measures, including biometric verification, one-time passwords (OTP), and challenge-response authentication for high-risk transactions; a self-learning and model-updating module configured to dynamically update fraud detection models using reinforcement learning and federated learning techniques; a data encryption and security module configured to protect transaction data using encryption techniques, including AES-256 and RSA, to prevent unauthorized access and data breaches; and A dashboard and reporting module configured to provide real-time analytics, visualizations, and fraud detection reports for financial institutions to monitor, track, and mitigate fraudulent activity.

The invention provides a power cable comprehensive online monitoring system, and relates to the technical field of data processing, and the system comprises the steps: extracting a partial discharge distribution point set in a multi-dimensional feature fusion data set, and calculating the weight factor of each distribution point; based on the weight factors, a weighted point set concave packet generation algorithm is adopted to construct a partial discharge source probability distribution boundary, and a boundary feature point set is obtained; inputting the boundary feature point set and the multi-dimensional feature fusion data set into a convolution-long and short-term memory hybrid neural network to generate a diagnosis result; and a third-level early warning signal is generated based on a diagnosis result, early warning information is pushed to a remote operation and maintenance terminal and a mobile APP through an MQTT protocol, a digital work order service is automatically triggered to generate a maintenance task, and positioning verification is executed. According to the invention, the accuracy of monitoring and fault diagnosis is improved.

The invention discloses a cattle and sheep farm feeding safety detection method and system based on real-time monitoring, and the method comprises the steps: installing a flow velocity sensor, a flow sensor and a pressure sensor at key positions of a feed conveying pipeline, obtaining the time sequence data of feed conveying in the pipeline, carrying out the preprocessing and feature extraction of the data, and carrying out the feature extraction of the data; and constructing a feed conveying state prediction model, performing online prediction on the conveying state in real time, and triggering early warning when the deviation between a predicted value and an actual value exceeds a threshold value. And specific abnormal types such as pipeline blockage, leakage or equipment failure can be judged by analyzing the change trend of the abnormal data. And abnormal information is pushed to operation and maintenance personnel through the mobile App to assist in quickly positioning and processing problems. According to the method, the model can be continuously optimized by using new abnormal data, the identification capability of different types of anomalies is improved, a decision basis is provided for pipeline maintenance, and the operation reliability and safety of the feed conveying pipeline are effectively improved.

The invention discloses an intelligent monitoring system and method based on the 5G Internet of Things, and relates to the technical field of intelligent monitoring, and the system comprises a data collection module, a data processing platform, a cloud server, an alarm module, a monitoring center and a mobile APP, and is used for solving the defects in the aspects of customer behavior prediction and supermarket safety in the prior art. A cloud platform management tool of the cloud server is used for monitoring the system state and the application program performance in real time, quickly responding to problems and regularly executing data cleaning and backup operations, so that the storage space is prevented from being excessively occupied; according to the method, time series, circulating network model deep learning and Internet of Things technologies are adopted, real-time monitoring and alarm mechanisms are combined, customer action tracks and customer behaviors are predicted and analyzed, appropriate supermarket layout and marketing strategies are formulated, meanwhile, abnormal behaviors can be rapidly and accurately recognized and processed, and the service life of the supermarket is prolonged. Therefore, the safety and management efficiency of supermarkets and supermarkets are effectively improved.

A system for monitoring and recording and processing an activity includes one or more cameras for automatically recording video of the activity. A processor and memory associated and in communication with the camera is disposed near the location of the activity. The system may include AI logic configured to identify a user recorded within a video frame captured by the camera. The system may also detect and identify a user when the user is located within a predetermined area. The system may include a video processing engine configured to process images within the video frame to identify the user and may modify and format the video upon identifying the user and the activity. The system may include a communication module to communicate formatted video to a remote video processing system, which may further process the video and enable access to a mobile app of the user.

The invention discloses a bucket wheel anti-collision system and an anti-collision method, and relates to the technical field of bucket wheel anti-collision. The system comprises a data acquisition module used for acquiring operation data, environment data and historical collision data of the bucket wheel machine, the operation data comprises the position, the speed, the angle and the operation mode of the bucket wheel machine, and the environment data comprises a coal yard three-dimensional map, obstacle coordinates and meteorological data; the historical collision data comprises accident records and false alarm analysis. The state and environment of the bucket wheel machine are mastered in real time through high-precision positioning and multi-mode sensing, collision is effectively prevented in combination with intelligent graded alarm, and safety is remarkably improved. The risk is predicted through big data analysis and machine learning, the operation path is dynamically adjusted, operation is optimized, the maintenance cost is reduced, and the service life of equipment is prolonged. Meanwhile, the cloud monitoring and the mobile terminal APP support remote operation and real-time information pushing, the convenience and applicability of the system are enhanced, and the management efficiency is improved.

The invention discloses a power equipment temperature monitoring and early warning system and method based on wireless communication, and relates to the technical field of temperature monitoring, the system comprises a wireless temperature measurement terminal box and a mobile terminal APP, the wireless temperature measurement terminal box and the mobile terminal APP establish communication connection based on a wireless network, and the wireless temperature measurement terminal box is fixedly installed on power equipment; the wireless temperature measurement terminal box comprises an electromagnetic environment judgment module which monitors and judges whether interference exists in the environment where power equipment is located in real time based on an electromagnetic sensor and synchronizes a result into a temperature drift compensation analysis module; and the temperature monitoring module monitors temperature data in the power equipment in real time based on a temperature sensor. Through electromagnetic environment judgment and temperature drift compensation, historical data and a model are combined to dynamically correct interfered temperature data, the influence of electromagnetic interference is eliminated, real-time monitoring is matched with graded alarm, hidden dangers can be found in time, response can be made according to risk grades, accidents are avoided, and wireless connection adapts to complex scenes.

The invention discloses an accumulation fund management system based on multivariate heterogeneous data fusion and a control method thereof, and relates to the field of accumulation fund management systems, and the system comprises a data access layer which is used for receiving various heterogeneous data sources of a bank end, an enterprise end and an accumulation fund management center end; the data fusion layer is used for performing data cleaning operation, data matching operation and data model construction operation on the heterogeneous data sources; the business processing layer is used for processing the accumulation fund core business; the data analysis layer and the business analysis layer are used for performing data analysis operation based on database storage data and user input data to generate an evaluation result; the security management layer is used for performing authority control operation on the access user, and the security management layer is also used for performing desensitization and encryption operation on the sensitive information; and the user service layer is used for providing mobile phone APP service, official account service and Web portal service.

The invention provides a gait detection and anomaly recognition system based on multi-sensor fusion, and the system comprises a sensor integration module which is used for deploying a thin film pressure sensor and a lightweight surface myoelectricity sensor and carrying out the data collection; the data preprocessing module is used for preprocessing the collected data; the feature extraction and fusion module is used for extracting and fusing features of the collected data to obtain a multi-modal feature vector; the gait monitoring module is used for constructing a recognition model; the abnormal recognition module is used for carrying out recognition and real-time feedback on abnormal gaits by utilizing a recognition model; and the doctor end interaction module is used for designing a mobile end APP and a doctor end management platform. According to the invention, through the multi-modal data and the portable wearable device, the diversity of detection modes is increased, the detection precision is improved, the method can be applied to multiple scenes, and the environmental limitation is broken; and meanwhile, by deploying a deep learning model, the intelligent degree of gait anomaly recognition is improved, and comprehensive technical support is provided for rehabilitation of the patient.

A system and method for control of a vehicle with a mobile app includes the configuration and providing of controllable vehicle components, a mobile device and a memory thereon containing a software to for determining if a malfunction has occurred in the control module of a vehicle, initiating vehicle control app on a mobile device, connecting to the mobile device, and allowing the mobile device to emulate and control the vehicle and its most vital components. The remote capability provided by interfacing with the vehicle's systems may be communicated wirelessly through protocols like Wi-Fi, Bluetooth, or Cellular, or through wired connections such as USB, the vehicle's OBD system, and AUX control. The system provides a redundant remote capability to a single point of failure for critical vehicle controls.

The invention discloses an intelligent early warning system for safety of buildings around foundation pit construction, and relates to the technical field of construction safety monitoring. The platform adopts a four-layer architecture of a sensing layer, a transmission layer, a platform layer and an application layer. The sensing layer collects data in real time through a multi-class sensor array; the transmission layer wirelessly transmits data by using the Internet of Things technology; the platform layer serves as a core, comprises a data management module, a digital twin modeling module and an intelligent analysis early warning engine, and is responsible for data preprocessing, three-dimensional model driving and intelligent risk study and judgment based on machine learning and a dynamic threshold value; and the application layer provides visual display and early warning push service through a Web terminal and a mobile APP. All-weather automatic monitoring, intelligent advanced early warning and accurate risk prevention and control of the surrounding environment of the foundation pit are achieved, a complete intelligent management closed loop is formed, and the construction safety level is effectively improved.

Cross-channel user authentication is provided, to increase resilience of a computerized system to cyber-attacks and to fraudulent transactions. In a demonstrative scenario, a user utilizes his web browser on his laptop computer to log-in to a web server; which in turn extracts the IP address of the laptop computer. The web server triggers an application server to send a Push Notification to a Mobile App that had been installed on a smartphone of that user who just logged in; and that Push Notification causes that smartphone to respond to the application server with the IP address of the smartphone. If the IP address of the computer is not identical to the IP address of the smartphone, then the servers determine that the log-in attempt on the computer was possibly fraudulent, and fraud mitigation operations are initiated. Optionally, geo-location data, device orientation data, device motion data, or other parameters are used as part of the cross-channel authentication process.

The invention belongs to the field of disease and pest recognition, and provides a potato disease recognition method based on improved YOLOV8. Firstly, early blight, late blight and healthy leaves of potatoes are collected, and then image preprocessing and feature region labeling are carried out; secondly, replacing an original backbone network with an OfficientViT structure, and introducing an SCSA collaborative attention module into an initial model network structure to optimize a YOLOV8 network model; secondly, training the optimized potato disease recognition model on the basis of a PyTorch framework, and setting proper model parameters and training times to enable the trained model to achieve higher recognition accuracy through verification; and finally, deploying the constructed potato disease identification model on a mobile terminal APP to realize real-time identification of field potato diseases, so that the invention provides a method capable of accurately and rapidly identifying potato diseases, which is beneficial to improving agricultural production efficiency and crop yield.

The invention discloses a bracelet for monitoring and improving exercise sleep quality and a use method thereof, and relates to the technical field of intelligent bracelets, the bracelet comprises a hardware part, the hardware part is an intelligent bracelet, and the intelligent bracelet comprises a sensor module used for collecting exercise data and sleep data of a user in real time; the control module is used for processing the motion data and the sleep data collected by the sensor module and obtaining the motion and sleep conditions of the user through algorithm analysis; and the communication module is used for sending the processed data to a matched mobile phone App and receiving improvement suggestions sent by the mobile phone App. Through a software and hardware combination mode, real-time monitoring and deep analysis of the exercise and sleep data of the user are realized, personalized exercise and sleep improvement suggestion guidance can be provided according to the actual condition of the user, so that the user can carry out effective living habit adjustment according to the bracelet data, and the user experience is improved. And a new solution is provided for improving the exercise and sleep quality of the user.

The present invention discloses a method for random on-site quality inspection, evaluation, acceptance and settlement based on BIM model, including: dividing engineering projects based on building information BIM model, defining unit engineering, sub-engineering, sub-project and unit engineering; using mobile terminal APP to inspect the quality of unit engineering, filling in inspection and evaluation materials through mobile terminal, and randomly sending them to relevant approvers for review, and obtaining the review results; based on the review results, measuring and verifying the corresponding unit engineering, uploading the engineering quantity calculation book, and associating and matching the unit engineering with the contract list, completing the approval process, and obtaining the measurement and verification sheet; selecting the measurement and verification sheet range, automatically generating contract settlement information, and visually displaying the settlement progress. The engineering quantity and quality of each unit can be more clearly determined, thereby optimizing the settlement process and reducing settlement disputes and disputes.

Disclosed herein are system, method, and computer program product embodiments for allowing completion of cardless transactions at a kiosk using an encoded identifier for that kiosk. A user of a mobile app may begin a transaction on their mobile device and, upon reaching a stage of the transaction where kiosk access is needed, receive instructions to visit a kiosk and scan the encoded identifier displayed by the kiosk. The scanned encoded identifier may be associated with the transaction, and the mobile app may transmit a request to complete the transaction at the kiosk.

The invention discloses a non-sensitive management control system and method for a shared office. The system comprises a mobile APP, a cloud management platform, an intelligent access control terminal, environment sensing equipment and an electrical control unit, through the management system integrating the mobile APP, the cloud management platform, the intelligent access control terminal, the environment sensing equipment and the electrical control unit, non-sensitive management of the shared office can be realized. According to the system, a tedious and low-efficiency application process is simplified, so that the employees can quickly complete office reservation, and the consumption of office time is remarkably reduced. Meanwhile, the system can dynamically adjust the electrical control unit according to real-time data provided by the environment sensing device, it is ensured that device operation is automatically closed or reduced in the unmanned period, energy waste is effectively avoided, and the operation cost is reduced. In addition, the resource utilization efficiency is improved through the fine management mode, administrative expenses caused by idle or overuse of resources are reduced, and therefore the operation efficiency of an enterprise is overall improved.

A lighted steering wheel device is provided. The device is comprised of a steering wheel that integrates customizable and functional lighting features to enhance both safety and aesthetics. The steering wheel comprises various materials and configurations, with embedded flexible LED strips encased in impact-resistant, UV-protected casings, capable of displaying a wide range of static or dynamic light patterns. These patterns can be synchronized with vehicle systems, such as flashing red for emergency braking or reacting to turn signals, and brightness can adjust based on vehicle speed. The device includes a control interface embedded in the wheel and offers further customization via a mobile app, which provides remote access to light settings and synchronization features. Additionally, the device can generate safety alerts, utilizing proximity sensors, GPS integration, and haptic feedback for a multisensory driver experience, with an illuminated emblem adding a complementary design element.

The invention discloses a human body action recognition method based on a single IMU (Inertial Measurement Unit) sensor. Comprising the following steps: acquiring data by adopting an IMU sensor at a fixed frequency, attaching an action category label, carrying out data noise reduction and normalization processing, delivering the data to a neural network model by utilizing a sliding window, training the neural network model, storing the model and uploading the model to a server, and obtaining a human body action recognition result by a mobile phone App. According to the recognition method, the memory ability of the neural network model to the action data time sequence is improved by using the BiLSTM, and the recognition precision is still very high under the condition that only one IMU sensor exists; meanwhile, an attention mechanism is added, significance features of the action data are extracted, context information of action data time sequences is obtained more comprehensively, the importance degree of local sequence features is learned, the influence of important time sequence features in the model is improved, and therefore the amount of information to be processed is reduced, the calculation load is relieved, and the real-time performance of recognition is ensured.

The present invention provides a method for connecting to a communication network associated with a micro market. The method includes scanning a code associated with an ephemeral app to be downloaded to a mobile communication device. In an example, the method includes associating a web address with a code to find the ephemeral app and linking the web address with the mobile device. In an example, the method includes transferring the ephemeral app in a first format using the Internet to a storage location on the mobile communication device, and initiating the ephemeral app onto the mobile device to open the ephemeral app. The method includes sensing for a Bluetooth beacon associated with a spatial area of one of the micro markets and connecting using the Internet to a server associated with the micro market to transfer the catalog and list of items associated with the micro market.

The invention discloses a cable trench fire monitoring and processing system, and the system comprises fire extinguishing balls which are disposed in a cable trench at intervals, and are used for triggering self-explosion and spraying a dry powder extinguishing agent when sensing a fire; the sensing module is integrated in the fire extinguishing ball system or near the fire extinguishing ball system, and is used for monitoring environmental parameters, gas concentration and fire conditions in the cable trench in real time, sending out an alarm signal according to a preset alarm threshold value, and triggering a lead in the fire extinguishing ball system after sensing that a fire occurs; and the communication module is connected with the sensing module and is used for wirelessly transmitting the monitoring data and the alarm signal to a remote system platform or a mobile phone APP. The invention further discloses a corresponding method and a storage medium. According to the invention, environmental parameters and gas content in the cable trench can be monitored in real time, fire hazards can be found in time, fire extinguishing measures can be taken automatically and rapidly, and the operation safety of a power system is effectively guaranteed.

The invention discloses an intelligent parking lot vehicle parking and searching management system, and the system comprises a parking lot gate system, a cloud server end, a parking lot parking space guiding map unit, and a mobile APP end. The cloud server side is used for receiving and transmitting data of the parking lot management system, the parking lot parking space guiding map unit is used for displaying parking lot parking space information data, and the mobile APP side is connected with the parking lot parking space guiding map unit through the cloud server side and used for obtaining parking lot parking space and vehicle positioning data at the mobile APP side. And the user parks and searches the vehicle according to the navigation route displayed on the interface of the mobile APP terminal. By arranging a series of structures, the vehicle, the user and the parking lot are positioned, the parking lot vehicle driving navigation route and the user vehicle searching navigation route are generated, accurate target data are obtained, the parking and vehicle searching time of the user in the parking lot is saved, and the parking lot management difficulty is reduced.

The invention provides a tomato disease identification method based on improved YOLOv8. The method belongs to the field of disease and pest identification, and comprises the following steps: firstly, collecting tomato disease images of different types including tomato early blight, late blight, leaf mold, spot blight, spot disease, mosaic virus and the like, and then carrying out image preprocessing and disease area labeling. And optimizing the YOLOV8 network model, wherein the optimization mainly comprises the step of introducing a MobileNetv4 model into an original network structure and the step of introducing an SEAM attention mechanism into an initial model network structure. Training the optimized tomato disease recognition model on the basis of a PyTorch framework, and setting proper model parameters and training times; and the trained model is verified to achieve relatively high recognition accuracy. And finally, deploying the constructed tomato disease identification model on a mobile terminal APP to realize real-time identification of field tomato diseases. The invention provides an accurate and rapid tomato disease identification tool, and aims to improve the agricultural production efficiency and the crop yield.

The invention discloses a network security monitoring system and method, belongs to the technical field of network security, and aims to solve the technical problem of how to carry out network security detection on an online internet financial website. Comprising a network threat discovery subsystem which is used for analyzing a network attack sample of the Internet financial platform, extracting an event rule, carrying out routing inspection on the Internet financial platform, discovering a network threat event aiming at the Internet financial platform based on the event rule and a routing inspection result, and recording the network threat event; the website vulnerability scanning subsystem is used for carrying out asset detection and vulnerability scanning on the Internet financial website to find security vulnerabilities; and the mobile APP security detection subsystem is used for performing security detection and risk analysis on the Internet financial mobile application to discover security vulnerabilities and transaction security risks.

The system provides a real-time video and audio communication with a 911 call center to perform effective CPR on a patient experiencing OHCA with real-time monitoring and feedback. The system includes a Mobile App that communicates with a smart phone with camera, a wireless remote-CPR equipment stand and emergency CPR kit. The mobile app will automatically send a link to a caregiver's cell phone responsive to a 911 call placed by the caregiver, to establish a secured video call via which the 911 center can guide the caregiver in performance of CPR until an ambulance arrives. This integrated description provides a comprehensive overview of the AI-driven CPR guidance system, detailing its core components, operational workflow, training processes, and scalability. By combining real-time coaching, advanced diagnostics, and EMS coordination, the system offers a groundbreaking approach to improving OHCA outcomes.

The invention discloses an industrial vehicle intelligent instrument control system and method based on multi-mode biological recognition, and the method comprises the following steps: S1, collecting fingerprint data of a driver, and carrying out the preprocessing; s2, fingerprint texture features are extracted, and weighted coding is carried out on local texture distribution and a global topological structure; s3, constructing an identity verification window, and performing bidirectional attention comparison on the fingerprint feature vector and the fingerprint template; s4, judging whether the identity verification is passed or not according to the similarity score, and if the verification is passed, triggering a buzzer or a voice broadcast device to generate control feedback; s5, starting the vehicle, awakening display, loading an instrument information page, and writing an identity verification result into a system buffer area; and S6, synchronizing an identity verification result to a mobile terminal APP or an applet platform through the Bluetooth MCU chip. According to the invention, industrial vehicle intelligent control based on fingerprint identification is realized, and the identity verification accuracy, the operation safety and the management efficiency are improved.

The invention relates to the technical field of information processing, in particular to a configurable electronic express sheet printing implementation method, device and equipment and a storage medium, by dynamically configuring an express sheet template, storing the express sheet template in a template library and importing the express sheet template into a cache, and preposing updating of the express sheet template, the flexibility is high, global controllability is achieved, the express sheet template can be updated to the whole network in time, and the efficiency is high. The method comprises the following steps of: shortening a processing period, receiving an order printing request instruction sent by a mobile APP, when the order printing request instruction needs to configure an express sheet, identifying a template format required in the order printing request instruction, calling a target template corresponding to the template format from a cache, extracting order information in the order printing request instruction, and filling the order information in the target template. According to the method, the filled template is obtained, the configuration printing instruction is generated according to the filled template, the new printing instruction is directly generated at the data generation end according to the newly added express sheet template, a new printing demand is quickly responded, the printing efficiency is improved, the user experience degree is improved, and the user satisfaction degree is improved.

A system for a mobile gift card marketplaces is disclosed. The system may initiate a contactless payment at a merchant via a mobile app. The system may receive an authorization message based on the contactless payment. The system may execute an authorization process in response to receiving the authorization message to determine an authorized transaction. The system may validate the authorized transaction to determine whether the authorized transaction is associated with a customer. The system may execute a merchant validation process to determine if the authorized transaction is associated with a merchant. The system may determine an available gift card account balance of the customer associated with the merchant in response to determining the authorized transaction is associated with both the customer and the merchant. The system may execute a gift card redemption process to redeem the available gift card account balance of the customer associated with the merchant.

A horticulture time lapse camera photo and sensor data capture system is disclosed. The horticulture time lapse camera photo and sensor data capture system is configured to capture time-lapsed photos and corresponding time-lapse series of sensor data, combine the photos in a video sequence, generate sensor data charts and visualizations, synchronize the collected data points and sensor data charts and visualizations to a timeline associated with a playback time of the video sequence, and provide the time-sequenced video for a user to view with the corresponding time-sequenced data points and sensor data graphical objects via mobile app or website. The system takes all parameters and sensor measurements and converts them into charts and graphs for viewing along with time-synchronized video sequences of the time-lapse photography, thereby providing valuable information for a user to remotely monitor plants and control the growing environment.