System and method for improving shelf life of perishable items

Abstract

The present disclosure relates to systems and methods for improving the shelf life of perishable items. A video-based system for controlling one or more environmental parameters of a food storage area of a facility may include a video camera and an environmental control system serving the food storage area of the facility. The video camera may include a camera housing, a camera housed by the camera housing for providing a video stream of a food storage area, a communication port for communicating with the environmental control system, and a controller housed by the camera housing and operably coupled to the camera and the communication port. The controller may be configured to analyze a video stream captured by the camera to identify a food product in the food storage area, identify one or more ideal food storage environmental parameters for the identified food product, and transmit the one or more ideal food storage environmental parameters for the identified food product to the environmental control system.

Description

Technical Field

[0001] The present disclosure generally relates to improving the shelf life of perishable items and, more particularly, to systems for controlling one or more environmental parameters of a storage area, including video-based systems. Background Art

[0002] Food waste is a global concern. The United Nations Environment Programme's Food Waste Index Report 2021 estimated that approximately 931 million tons of food waste were generated in 2019. Common foods, such as but not limited to rice, wheat, millet, legumes, etc., should be stored at specific temperatures and relative humidities to extend the shelf life of the items. For example, food spoilage may occur when food is not stored under appropriate environmental conditions during transportation, storage, etc. Food waste can lead to problems that have an impact on the environment, economy, and / or society. Food production requires substantial resources, such as water, land, and energy. When food is wasted, these valuable resources are also wasted. This can lead to resource depletion and inefficiencies in the food system. Additionally, while food is being wasted, millions of people worldwide suffer from hunger and food shortages. By reducing food waste, surplus food can be redistributed to those in need, thus helping to alleviate hunger. Further, food waste can generate a significant carbon footprint. When food decomposes in landfills, the food may produce methane, which is a potent greenhouse gas that contributes to climate change.

[0003] In addition, food waste can cause significant economic losses to consumers, businesses, and governments. For example, when resources invested in food production, transportation, and retail are wasted, consumers, businesses, and governments may suffer economic losses. Food waste can also raise ethical issues as it may highlight the imbalance between food abundance in some regions and food shortages in other regions. In some examples, food production may involve the conversion of natural habitats to farms. This can lead to a loss of biodiversity. Food waste can exacerbate the environmental impacts associated with food production and land use. Discarded food can lead to unhygienic conditions and may attract pests. Unhygienic conditions and / or pests can pose potential health risks to humans. Food waste can occur at various stages of the supply chain, including but not limited to agricultural production, processing, distribution, retail, end consumers, etc. What is desired are methods and systems for improving the monitoring and control of environmental conditions in food storage areas. Summary of the Invention

[0004] The present disclosure generally relates to systems and methods for improving the shelf life of perishable items such as food products, chemical products, healthcare products, pharmaceutical products, etc.

[0005] One example of the present disclosure includes a method for controlling one or more environmental parameters of a food storage area of a facility. The exemplary method includes capturing video of the food storage area of the facility using a video camera. The video camera itself may be configured to: identify food items in the captured video of the food storage area, identify one or more ideal food storage environmental parameters for the identified food items, and transmit the identified one or more ideal food storage environmental parameters from the video camera to an environmental control system of the facility serving the food storage area. The exemplary method may further include controlling the environmental control system of the facility based on the one or more ideal food storage environmental parameters transmitted by the video camera to the environmental control system. By having a video camera with built-in algorithms (artificial intelligence, machine vision, and / or other algorithms), a system for appropriately controlling the environmental parameters of one or more food storage areas or zones of a facility can be easily deployed. The built-in algorithms identify food items contained in the video captured by the video camera and identify ideal food storage environmental parameters (e.g., temperature setpoint, relative humidity setpoint) for the identified food items and transmit the identified ideal food storage environmental parameters to the HVAC / refrigeration system to control the environment for storing the food items.

[0006] In another example, a video camera for a food storage area may include: a camera housing; a camera housed by the camera housing that provides a video stream of the food storage area; and a controller housed by the camera housing and operably coupled to the camera. The controller may be configured to analyze the video stream captured by the camera to identify food items in the food storage area, obtain one or more ideal food storage environmental parameters for the identified food items, and transmit the one or more ideal food storage environmental parameters to an environmental control system serving the food storage area.

[0007] In another example, a video-based system for controlling one or more environmental parameters of a food storage area of a facility may include a video camera that captures a video stream of the food storage area of the facility and an environmental control system serving the food storage area of the facility. The video camera may include a camera housing, a camera housed by the camera housing for providing a video stream of the food storage area, a communication port for communicating with the environmental control system, and a controller housed by the camera housing and operably coupled to the camera and the communication port. The controller may be configured to analyze the video stream captured by the camera to identify food items in the food storage area, identify one or more ideal food storage environmental parameters for the identified food items, and transmit the one or more ideal food storage environmental parameters for the identified food items to the environmental control system via the communication port.

[0008] The foregoing Summary is provided to facilitate an understanding of some of the innovative features unique to the present disclosure and is not intended as a complete description. A full understanding of the present disclosure can be obtained by viewing the entire specification, claims, drawings, and abstract as a whole. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The present disclosure can be more fully understood in consideration of the following description of various examples in conjunction with the accompanying drawings, in which:

[0010] Figure 1 is a schematic block diagram of an exemplary video-based system for controlling one or more environmental parameters of a food storage area of a facility;

[0011] Figure 2 is a flowchart of an exemplary method for controlling one or more environmental parameters of a storage area of a facility; and

[0012] Figure 3 is a flowchart of an exemplary method for generating one or more food recognition models.

[0013] While the present disclosure is subject to various modifications and alternative forms, specific details thereof have been shown by way of example in the drawings and will be described in detail. It should be understood, however, that the intention is not to limit the present disclosure to the particular examples described. On the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosure. DETAILED DESCRIPTION

[0014] The following description should be read with reference to the drawings, in which like elements in different drawings are numbered in the same manner. The drawings are not necessarily to scale and depict examples that are not intended to limit the scope of the present disclosure. While examples of various elements are illustrated, those skilled in the art will recognize that many of the examples provided have suitable alternatives that can be utilized.

[0015] It is assumed herein that all numbers are modified by the term "about" unless the context clearly dictates otherwise. The recitation of numerical ranges by endpoints includes all numbers subsumed within that range (e.g., 1 to 5 includes 1, 1.5, 2, 2.75, 3, 3.80, 4, and 5).

[0016] As used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. As used in this specification and the appended claims, the term "or" is generally employed in its sense including "and / or" unless the context clearly dictates otherwise.

[0017] It should be noted that when "an embodiment", "some embodiments", "other embodiments", etc. are mentioned in the specification, it indicates that the described embodiments may include specific features, structures, or characteristics, but each embodiment may not necessarily include the specific feature, structure, or characteristic. Moreover, these phrases do not necessarily refer to the same embodiment. Additionally, when a specific feature, structure, or characteristic is described in connection with an embodiment, it is contemplated that the feature, structure, or characteristic is described in connection with an embodiment, and it is contemplated that the feature, structure, or characteristic can be applied to other embodiments whether or not it is explicitly described, unless there is a clear contrary indication.

[0018] Figure 1 is a schematic block diagram of an exemplary video-based system 10 that can utilize one or more cameras 16a-n to control one or more environmental parameters of one or more food storage areas 14a-n of a facility 12. Although the present disclosure is discussed with respect to food storage, it should be understood that the present system and method can be used in other applications where items may be perishable or require specific storage conditions. For example, the present system and method can be used for the storage of chemical products, health care products, and pharmaceuticals in hospitals, pharmacies, homes, industrial facilities, etc. during the transportation of the products. One or more cameras 16a-n can be positioned within the storage areas 14a-n. In some cases, each storage area 14a-n can have one or more of its own unique cameras 16a-n. Each camera 16a-n of the one or more cameras can have a field of view that covers at least a portion of the corresponding storage area 14a-n. When more than one camera 16a-n is provided, the fields of view of the cameras can overlap or cover separate and distinct areas as needed. It is contemplated that the storage areas 14a-n can include the desired number of cameras such that at least one field of view covers each different storage area 14a-n.

[0019] The video cameras 16a-n may each include a housing 18a-n for enclosing the components of the video cameras 16a-n. The housing 18a-n may include a plurality of components configured to be fixed to each other. In some cases, the video cameras 16a-n may be dome cameras including a transparent protective dome. However, this is not required. In some cases, the video cameras 16a-n may be bullet cameras. The video cameras 16a-n may have a fixed field of view as needed or may be pan-tilt-zoom (PTZ) cameras. It is contemplated that the video cameras 16a-n may be used indoors and / or outdoors as needed, and for day and / or night use. In some cases, the housing 18a-n may be weatherproof for outdoor use and / or one or more night vision light-emitting diodes (LEDs) may be provided for night use. The video cameras 16a-n may include additional structural and / or functional elements of a video camera not described herein, but for clarity only some elements are shown / described.

[0020] Within the housing 18a-n, an exemplary video camera 16a-n can include or house a lens. The lens may be configured to direct incident light towards an image sensor (not explicitly shown). The image sensor may process the light captured by the lens into a digital signal. This digital signal (e.g., video recording) may be stored in the memory 22a-n of the video camera 16a-n and / or transmitted to a video management system (VMS), network video recorder (NVR), and / or other edge devices. In some cases, the image sensor may be provided as part of a control printed circuit board, but this is not required. The control printed circuit board may include a processor or controller 20a-n. Although some components are described as part of the control printed circuit board, these components may be provided separately from the control printed circuit board. In some cases, the controller 20a-n may be configured to analyze an image, match the image to a product, identify ideal environmental parameters for storing the product, and transmit the ideal environmental parameters to the environmental control system 30, as will be described in more detail herein. The controller 20a-n may also communicate with or be operatively coupled to the memories 22a-n. The memories may be used to store any desired information, such as but not limited to machine instructions for how to process data from the image sensor, a database of items that can be stored in the facility 12, ideal environmental parameters for the items, etc. The memories may be any suitable type of storage device, including but not limited to RAM, ROM, EPROM, flash memory, hard disk drives, etc. In some cases, the controller environmental parameters and / or the image sensor may store information in the memory 22a-n and subsequently retrieve the stored information from the memory.

[0021] In some embodiments, the video cameras 16a-n may be equipped with communication modules 24a-n. The communication modules 24a-n may allow the video cameras 16a-n to communicate with other components of the facility, such as but not limited to the environmental control system 30, network video recorder (NVR), etc. The communication modules 24a-n may provide wired and / or wireless communication. In one example, the communication modules 24a-n may use any desired wireless communication protocol as needed, such as but not limited to cellular communication, ZigBee, REDLINK TM , Bluetooth, WiFi, IrDA, dedicated short-range communication (DSRC), EnOcean, and / or any other suitable public or proprietary wireless protocol. In another example, the communication modules 24a-n may communicate via a network cable. In some cases, the network cable may be a power over Ethernet (POE) cable. Exemplary video cameras 16a-n may receive power via a POE cable, a separate power cable, a battery, or any other suitable power source as needed.

[0022] Exemplary video cameras 16a-n may also include a rear frame. The rear frame may form part of the housing 18a-n or may be mounted to the housing 18a-n to mount the video camera 16a-n to a wall or ceiling. In some cases, the rear frame may be coupled to the outside of the housing 18a-n, while in other cases, the rear frame may be located inside or within the housing 18a-n. In some cases, the rear frame may accommodate cable connectors. For example, the rear frame may accommodate a connector between a network cable and the control printed circuit board 20a-n, a connector between a power cable and the control printed circuit board 20a-n, and / or a connector between an audio cable and the control printed circuit board 20a-n. It is contemplated that the video cameras 16a-n may include other cables and / or connectors as needed. In some cases, the internal circuitry of the connection ports within the rear frame may be used to test the connection between the video camera 16a-n and the network. The ports may include LEDs that emit light of a certain color to indicate connectivity.

[0023] The video cameras 16a-n may also include barcode scanners 26a-n. The barcode scanners 26a-n may be configured to scan barcodes on packaged items and transmit data to the processor / controller 20a-n. The processor / controller 20a-n may use the data from the scanned barcode to assist in identifying the scanned item. In some cases, the processor / controller 20a-n may digitally process the video stream captured by the camera and identify and read barcodes on items captured in the video stream, rather than including a separate barcode scanner.

[0024] Alternatively or additionally, the video cameras 16a-n may include radio frequency identification (RFID) scanners 28a-n. The RFID scanners 28a-n may be configured to read RFID chips that may be included with the food. For example, the RFID chips may be affixed to a tray, positioned within a crate or box, or otherwise associated with the packaging of the food. The RFID chips may store information related to the actual food product, the type of food product, ideal environmental parameters for its storage, and the like.

[0025] Video cameras 16a-n can communicate with a controller 32 of an environmental control system 30, which is configured to serve food storage areas 14a-n of a facility 12. The controller 32 can be configured to receive data from the video cameras 16a-n, analyze the data, and make decisions based on the data. For example, the controller 32 can include control circuitry and logic components that are configured to operate, control, command, etc. various components of environmental control system devices 46 of the environmental control system 30 and / or issue alerts or notifications. In some examples, the environmental control system devices 46 can be part of one or more heating, ventilation, and air conditioning (HVAC) systems and / or one or more refrigeration systems (e.g., climate control for a refrigerator or freezer / system). The environmental control system 30 can include any number of system devices or apparatuses 46. Some illustrative apparatuses can include, but are not limited to, furnaces, heat pumps, electric heat pumps, ground source heat pumps, electric heating units, air conditioning units, rooftop units, humidifiers, dehumidifiers, air exchangers, air purifiers, dampers, valves, blowers, fans, motors, air washers, ultraviolet (UV) lights, compressors, condensers, evaporators, etc. The environmental control system 30 can also include a duct system and vents (not explicitly shown). In some examples, the environmental control system devices 46 can be configured to control one or more zones 50a-n. In some cases, the zones 50a-n can be related or associated with corresponding storage areas 14a-n. For example, each zone 50a-n or storage area 14a-n can be controlled according to its own unique setpoint. The environmental control system 30 can also include one or more sensors or devices 48 that are configured to measure parameters of the environment to be controlled. The environmental control system 30 can include more than one of each type of sensor or device as needed to control the system. It is contemplated that large buildings (such as, but not limited to, warehouse buildings) can include multiple different sensors in each room, in different areas of a larger room, and / or in certain types of rooms. For example, one or more sensors 48 can be positioned within each storage area 14a-n to collect data related to the specific storage area 14a-n in which the sensor 48 is located. One or more sensors or devices 48 can include, but are not limited to, temperature sensors, humidity sensors, carbon dioxide sensors, pressure sensors, occupancy sensors, proximity sensors, etc. Each of the sensors / devices 48 can be operably connected to the control device 32 via a corresponding communication port (not explicitly shown). It is contemplated that the communication port can be wired and / or wireless. In the case where the communication port is wireless, the communication port can include a wireless transceiver, and the control device 32 can include a compatible wireless transceiver. It is contemplated that the wireless transceiver can communicate using standard and / or proprietary communication protocols.As needed, suitable standard wireless protocols may include, for example, cellular communication, ZigBee, Bluetooth, WiFi, IrDA, dedicated short range communication (DSRC), EnOcean, or any other suitable wireless protocol.

[0026] Controller 32 may communicate with any number of video cameras 16a-n as needed, such as but not limited to one, two, three, four, ten, one hundred, or more video cameras. In some cases, there may be more than one controller 32, each controller communicating with multiple video cameras 16a-n. For example, a large facility 12 may have more than one HVAC system, more than one refrigeration system, a combination of an HVAC system and a refrigeration system, etc., all of which may be controlled by separate controllers, or a group of devices may be controlled by a common controller. It is contemplated that the number of video cameras 16a-n may depend on the size and / or function of the facility 12. The video cameras 16a-n may be selected and configured to monitor different aspects or locations of the building and / or area of the facility 12.

[0027] Controller 32 may be configured to communicate with the video cameras 16a-n, the environmental control system devices 46, and / or the sensors 48 via a first network 34 including a local area network (LAN) or a wide area network (WAN), or may establish a connection to an external computer (e.g., via the Internet using an Internet service provider). Such communication may be performed via a first communication port 36 at the controller 32, communication modules 24a-n at the video cameras 16a-n, and communication modules (not explicitly shown) at the system devices 46 and / or the sensors 48. The first communication port 36 of the controller 32 and / or the communication modules 24a-n of the video cameras 16a-n, the system devices 46 and / or the sensors 48 may be wireless communication ports including wireless transceivers for wirelessly transmitting and / or receiving signals via a wireless network. However, this is not required. In some cases, the first network 34 may be a wired network or a combination of a wired network and a wireless network.

[0028] Although not explicitly shown, the controller 32 may include a second communication port, which may be a wireless communication port including a wireless transceiver for transmitting and / or receiving signals via a second wireless network. However, this is not necessary. In some cases, the second network may be a wired network or a combination of a wired network and a wireless network. In some embodiments, the second communication port may communicate with a wired or wireless router or gateway for connection to the second network, but this is not necessary. When so provided, the router or gateway may be integral with the controller 32 (e.g., within the controller), or may be provided as a separate device. The second network may be a wide area network or a global network (WAN), including, for example, the Internet. The controller 32 may communicate with external web services hosted by one or more external web servers (e.g., the cloud) via the second network.

[0029] The controller 32 may include a processor 38 (e.g., a microprocessor, a microcontroller, etc.) and a memory 40. In some cases, the controller 32 may include a user interface 42, which includes a display and means for receiving user input (e.g., a touch screen, buttons, a keyboard, etc.). In some cases, the user interface 42 may be integral with the controller 32. Alternatively or additionally, the controller 32 may be operably coupled to a remotely located user interface, which includes a display and means for receiving user input. For example, the remotely located user interface may be a display in a facility monitoring station, a portable device (such as but not limited to a smart phone, a tablet computer, a laptop computer, etc.) or other such device. It is contemplated that the remote user interface may communicate with the controller 32 via the first network 34 and / or the second network as needed.

[0030] The memory 40 may communicate with the processor 38. The memory 40 may be used to store any desired information, such as but not limited to control algorithms, configuration protocols, set points, scheduling times, diagnostic limits (such as, for example, differential pressure limits, ΔT limits), security system arming modes, audio classification models, etc. In some embodiments, the memory 40 may include a specific control program or module configured to analyze data obtained from the video cameras 16a-n for specific conditions or situations, but this is not necessary. The memory 40 may be any suitable type of storage device, including but not limited to RAM, ROM, EPROM, flash memory, a hard disk drive, etc. In some cases, the processor 38 may store information in the memory 40 and may subsequently retrieve the stored information from the memory 40.

[0031] In some embodiments, the controller 32 may include an input / output block (I / O block) 44 having a plurality of terminals for receiving one or more signals from the video cameras 16a-n and / or system components and / or for providing one or more control signals to the video cameras 16a-n and / or system devices 46. For example, the I / O block 44 may communicate with one or more components of the system 10, including but not limited to the video cameras 16a-n and / or environmental control system devices 46 (e.g., heating, cooling, humidity control, refrigeration, ventilation, etc.). The controller 32 may have any number of terminals for receiving connections from one or more components of the system 10. However, the number of terminals used and which terminals are wired depends on the specific configuration of the system 10. Different systems 10 with different components and / or component types may have different wiring configurations. In some cases, the I / O block 44 may be configured to receive wireless signals from the video cameras 16a-n and / or one or more components or sensors (not explicitly shown). Alternatively or additionally, the I / O block 44 may communicate with another controller. It is further contemplated that the I / O block 44 may communicate with another controller that controls a separate building control system, such as but not limited to an HVAC controller, a refrigeration system controller, etc.

[0032] The controller 32 may also include one or more sensors, such as but not limited to a temperature sensor, a humidity sensor, an occupancy sensor, a proximity sensor, etc. In some cases, the controller 32 may include an internal temperature sensor 50, but this is not required.

[0033] When so provided, the user interface 42 may be any suitable user interface 42 that allows the controller 32 to display and / or request information and accept one or more user interactions with the controller 32. For example, the user interface 42 may allow the user to locally input data (such as control setpoints, start times, end times, scheduling times, diagnostic limits, responses to alerts), associate sensors with alert modes, etc. In one example, the user interface 42 may be a physical user interface accessible at the controller 32 and may include a display and / or a different keypad. The display may be any suitable display. In some cases, the display may include or may be a liquid crystal display (LCD), and in some cases may include or may be an electronic ink display, a fixed segment display, or a dot matrix LCD display. In other cases, the user interface may be a touchscreen LCD panel that serves as both a display and a keypad. The touchscreen LCD panel may be adapted to request values of multiple operating parameters and / or receive such values, but this is not required. In other cases, the user interface 42 may be a dynamic graphical user interface.

[0034] In some cases, the user interface 42 does not require the user to have physical access at the controller 32. Instead, the user interface can be a virtual user interface 42 that can be accessed via the first network 34 and / or the second network using a mobile wireless device (such as a smart phone, tablet computer, e-reader, laptop computer, personal computer, key card, etc.). In some cases, the virtual user interface 42 can be provided by one or more apps that are executed by the user's remote device for the purpose of remotely interacting with the controller 32. Through the virtual user interface 42 provided by the app on the user's remote device, the user can change control setpoints, start times, end times, scheduling times, diagnostic limits, responses to alerts, update their user profile, view energy usage data, arm or disarm the security system, configure the alarm system, etc.

[0035] As described above, the controller 32 can alternatively or additionally communicate with a remote user interface or display device via the first network and / or the second network 34. The remote user interface can be located, for example, in a control room, main office, monitoring station, etc. Alternatively or additionally, the remote user interface can be a portable device carried by the user (e.g., a smart phone, tablet computer, laptop, watch, etc.). The remote user interface can be a physical device or a virtual user interface (e.g., accessible via the Internet) as described above. In some cases, the remote user interface can include a display and / or a different keypad. The display can be any suitable display. It is contemplated that in addition to communicating with the controller 32, the remote user interface can also communicate with other building control devices or systems including the video cameras 16a-n.

[0036] Figure 2 is a flowchart of an exemplary method 100 for controlling one or more environmental parameters of the storage areas 14a-n of the facility 12. For simplicity, method 100 will be described with respect to a particular video camera 16a that monitors a particular storage area 14a. However, it should be understood that method 100 can be performed on more than one storage area 14a-n substantially simultaneously. Although method 100 is described with respect to food, food storage, etc., it should be understood that the method can be used to identify other items and / or other locations as needed. The video camera 16a captures video of the food storage area 14a, as shown in block 102. The captured video stream can be high resolution to provide clear and detailed images for analysis. The processor 20a of the video camera 16a can analyze the video stream to identify at least one food item in the captured video, as shown in block 104.

[0037] It is contemplated that the processor 20a may be configured to identify food using a variety of different techniques. In a first example, the memory 22a may store a food recognition module that is configured to analyze images from the video camera 16a to identify the type of food in the images. The food recognition module may include one or more models for identifying food. In some examples, the one or more models may be artificial intelligence (AI) models that are pre-trained before being loaded into the memory 22a of the video camera 16a. Alternatively or additionally, the one or more models may be trained for a specific facility 12 or a specific storage area 14a. The one or more models may be pre-trained or trained using deep neural artificial intelligence (AI) training, such as Figure 3 shown in

[0038] reference Figure 3 , which is a flowchart of an exemplary method 200 for generating one or more AI models for food recognition. Different data sets of food images are collected or acquired, as shown in block 202. The images represent various food types, various food quality levels, various food amounts, various food packages, safety conditions (e.g., open packaging, improper packaging, cross-contamination, etc.). In some examples, the selected images may be generic for multiple different storage facilities. In other examples, the images may be specifically selected for a particular storage facility or for a specific storage area of a facility. Once the images are collected or obtained, the images may be annotated with relevant labels, as shown in block 204. Some exemplary labels may include, but are not limited to, good, spoiled, contaminated, improperly packaged, food type, food category, food amount, etc. The labels may be used to create ground truth data for training the food recognition AI models.

[0039] Then, an annotated dataset (e.g., annotated images) can be used to train an AI model or AI engine, as shown in block 206. The AI engine can be trained to recognize the shape of the food, the labels present on the food, the volume of the food, the barcodes present on the food, and / or any other suitable food characteristics. Training the AI model can include providing the model with labeled (annotated) images and allowing the model to learn patterns and features for accurate recognition and / or classification. Once the AI model is trained, the trained AI model can be integrated into the video cameras 16a-n, as shown in block 208. It is contemplated that the trained AI model can be stored in the memories 22a-n of the video cameras 16a-n so that the processors 20a-n can access the food recognition model. Then, the food recognition model can be tested and verified to ensure its accuracy and effectiveness at the installation site, as shown in block 210. For example, the video cameras 16a-n can be used to capture images of known foods and known food qualities. The recognized food type and quality are output by the food recognition model and can be compared with the actual food and quality to verify the accuracy of the food recognition model. If the accuracy meets or exceeds a predetermined threshold (e.g., a predetermined percentage of accurately recognizing the food, quality, etc.), the video cameras 16a-n can be deployed in the facility 12 or other monitoring locations, as shown in block 212. If the accuracy does not meet the predetermined threshold, additional food images can be obtained, annotated, and incorporated into the training of the AI model. These steps can be repeated until the accuracy meets or exceeds the predetermined threshold. Once the video cameras 16a-n have been deployed, the performance of the food recognition model can be routinely monitored to ensure that it continues to function adequately, as shown in block 214. If the performance of the food recognition module degrades, additional food images can be obtained, annotated, and incorporated into the training of the AI model to improve its accuracy.

[0040] Return to Figure 2 , it is contemplated that the processor 20a of the video camera 16a can interpret and process the images captured by the video camera 16a to use a variety of different algorithms and / or techniques (including reference Figure 3The described AI model) is used to identify food 104. Some exemplary computer vision algorithms and / or techniques that can be used include, but are not limited to, image filtering (e.g., blurring, sharpening, and edge detection to enhance or extract specific features in an image), object detection (e.g., often using bounding boxes to identify and locate objects in an image or video stream), image classification (e.g., training an AI model to classify an image into predefined categories or labels, such as differentiating between different objects or scenes), semantic segmentation (e.g., dividing an image into several regions and assigning each pixel to a specific category, which helps understand the structure of the image), optical character recognition (OCR) (e.g., identifying text in an image and converting it into an editable and machine-readable format), feature detection and matching (e.g., identifying unique points or features in an image and finding their corresponding matches on multiple images), image super-resolution (e.g., a technique for magnifying a low-resolution image while preserving or enhancing details), pose estimation (e.g., determining the pose or orientation of an object or person in an image or video), image registration (e.g., aligning multiple images taken from different viewpoints or times to create a coherent representation), tracking (e.g., following the movement of an object or person in consecutive frames of a video), and so on. It is contemplated that any one or combination of the above algorithms or techniques can be used to identify the food captured in the image. For example, tracking can be used to determine that an item is entering the storage area 14a and trigger the analysis of the item. However, this is not necessary. Optical character recognition (OCR) can be used to identify the words on the food packaging or label, while image classification can be used to determine the quality of the food. These are just some examples. In some cases, the image recognition module can be set with more than one type of model to help identify the food type and / or quality.

[0041] Generally, the controller 20a of the video camera 16a can be configured to analyze the video stream or image captured by the video camera 16a to identify the shape of the food, the color of the food, the type of the food, the presence or absence of outer packaging, the quality of the food, the presence or absence of a label, the presence or absence of a barcode, etc. In some cases, the controller 20a can be configured to use multiple different identification techniques to identify the food. For example, the controller 20a can be configured to first attempt to identify the barcode or RFID tag attached to the food. If the barcode or RFID tag is unavailable or unreadable, the controller 20a can be configured to identify the label. The controller 20a can sequentially use different identification techniques until the food is identified. Alternatively, different identification techniques can be executed in parallel. When the food includes label information, identifying the food 104 can include identifying the label of the food in the captured video of the food storage area and comparing the label information of the label with a database of foods to identify the food. When the food is packaged with a barcode, identifying the food 104 can include identifying the barcode of the food in the captured video of the food storage area and decoding the barcode to identify the food. In some examples, the barcode scanner 26a can be used to decode the barcode. In other examples, when the food is packaged with an RFID tag, identifying the food 104 can include reading the RFID tag at the RFID scanner 28a. When the identified food has a shape and / or color, identifying the food can include identifying the shape and / or color of the food in the captured video of the food storage area and comparing the shape and / or color with a database of food shapes and colors to assist in identifying the food. Various databases (e.g., food labels, barcodes, shapes, etc.) can be stored in the memory 22a of the video camera 16a as needed, or can be stored in a remote device accessible via a wired network or a wireless network.

[0042] Once the food and / or its quality has been identified, the processor 20a of the video camera 16a can identify one or more ideal food storage environment parameters for the identified food, as shown in block 106. In some cases, the processor 20a can access a database that includes a list of foods and one or more corresponding ideal food storage environment parameters. The database can be stored in the memory 22a of the video camera 16a as needed, or can be stored in a remote device that can be accessed via a wired or wireless network. In some examples, one or more ideal food storage environment parameters can be one or more of a temperature setpoint, a relative humidity (RH) setpoint, etc. Appropriate temperature and RH can be important for maintaining the quality and safety of food through techniques such as refrigeration, freezing, and dehydration. It is contemplated that the temperature of the surrounding environment and / or the relative humidity of the surrounding environment may affect the quality, safety, and shelf life of various types of food products. For example, temperature and relative humidity may affect: microbial growth (e.g., high temperature and / or high RH can create favorable conditions for the growth of bacteria, mold, and yeast, leading to food spoilage and potential foodborne illness), food spoilage (e.g., improper storage temperature and high humidity levels can accelerate food spoilage, resulting in changes in the texture, appearance, taste, and aroma of the food product), enzymatic reactions (e.g., temperature and RH can affect enzymatic reactions in food, leading to adverse changes in color, flavor, and nutritional content), chemical reactions (e.g., temperature can trigger chemical reactions such as oxidation, which can have a negative impact on the quality and nutritional value of food), food texture and / or appearance (e.g., temperature can affect the texture and appearance of various food products: low temperature can affect the texture of fruits and vegetables, while high temperature can cause chocolate and confections to melt or deform), and so on.

[0043] In addition, for perishable goods such as fruits, vegetables, and dairy products, it may be important to maintain an appropriate temperature during transportation and storage to prevent spoilage and / or extend the shelf life. For humidity-sensitive foods such as grains, cereals, and snacks, controlling the RH to prevent caking, mold growth, and / or spoilage may be important. Additionally, improper temperature control during food processing, storage, and / or transportation can lead to the growth of pathogens and increase the risk of foodborne illness. It is also contemplated that maintaining an appropriate temperature and RH for food can help maintain the nutritional content of the food during processing and storage.

[0044] Once the controller 20a of the video camera 16a has identified and / or obtained one or more desired food storage environment parameters, the controller 20a can transmit the one or more desired food storage environment parameters to the environmental control system 30, as shown in block 108. The controller 32 of the environmental control system 30 can then control the environmental control system 30 based on the one or more desired food storage environment parameters. For example, the controller 32 of the environmental control system 30 can control the environmental control system equipment 46 associated with the storage area 14a such that one or more environmental parameters (e.g., temperature, relative humidity, etc.) of the storage area 14a match the one or more desired food storage environment parameters for the food in the particular storage area 14a, as shown in block 110. This may include heating, cooling, humidifying, dehumidifying, etc. In some cases, the environmental control system 30 can be configured to transmit one or more measured environmental parameters of the food storage area 14a to the video camera 16a. In other words, one or more measured environmental parameters (e.g., temperature, relative humidity, etc.) of the food storage area 14a can be received by the video camera.

[0045] Optionally, the controller 20a of the video camera 16a can analyze the available space in the storage area 14a. For example, the controller 20a can be configured to analyze the video stream captured by the camera 16a to identify the amount of space in the food storage area occupied by food products. The amount of space occupied by food products can be related to the amount of food stored in the food storage area 14a and can facilitate inventory control. Alternatively or additionally, the controller 20a can be configured to analyze the video stream captured by the video camera 16a to identify the amount of unoccupied space in the food storage area 14a. The amount of unoccupied space can be used to determine how many additional food products can be placed in the food storage area 14a or to assist with inventory control.

[0046] In some cases, the video camera 16a can identify food and can refer to a remote database to identify the ideal environmental parameters for that food. In some cases, the video camera 16a can identify food, send the identified food to a remote device, the remote device identifies the ideal environmental parameters for the identified food and returns them to the video camera, and then the video camera notifies the environmental control system to appropriately control the food storage area 14a. In some cases, the video camera 16a can identify food and then send the identified food to a remote device, the remote device identifies the ideal environmental parameters for the identified food and notifies the environmental control system to appropriately control the food storage area 14a. In some cases, the video camera 16a can identify food, identify the ideal environmental parameters for the identified food, and send control commands directly to environmental control devices (e.g., rooftop units, dehumidifiers, humidifiers, etc.) to control the environmental conditions in the food storage area, thereby performing some or all of the functions of the environmental control system 30. These are just examples.

[0047] Conceivably, a video-based system 10 for controlling one or more environmental parameters of a food storage area 14a-n of a facility 12 may have advantages that contribute to food safety, waste reduction, and overall environmental and social benefits. Some exemplary advantages may include, but are not limited to: food safety (e.g., sustainable food handling practices can prioritize hygiene, proper storage, and temperature control, thereby reducing the risk of foodborne illnesses and ensuring consumer safety), waste reduction (e.g., through effective management of food storage and inventory, sustainable food handling can help minimize food waste and associated economic and environmental impacts), resource conservation (e.g., sustainable food handling can optimize the use of resources such as water, energy, and packaging materials, thereby reducing resource consumption and promoting environmental protection), energy efficiency (e.g., implementing energy-saving practices in food handling, such as using energy-efficient appliances and refrigeration systems, can reduce energy consumption and greenhouse gas emissions), responsible packaging (e.g., sustainable food handling can encourage the use of environmentally friendly and recyclable packaging materials, thereby reducing plastic waste and environmental pollution), local sourcing (e.g., emphasizing local sourcing and shorter supply chains in food handling can support local farmers and producers, reduce transportation-related emissions, and enhance food safety), reduced chemical use (e.g., sustainable food handling can promote alternatives to chemical preservatives and additives, thereby minimizing potential hazards to human health and the environment), social and ethical considerations (e.g., sustainable food handling practices can prioritize fair labor practices, worker safety, and ethical treatment of employees in the food supply chain), innovation and technology (e.g., adopting sustainable food handling can encourage the use of innovative technologies that can improve efficiency and reduce environmental impacts), compliance with regulations (e.g., sustainable food handling practices can meet and often exceed food safety and environmental regulations, thereby ensuring compliance and responsible business conduct), consumer trust (e.g., sustainable food handling can promote consumer trust and loyalty because it can demonstrate a commitment to social and environmental responsibility), adaptability to disruptions (e.g., sustainable food handling practices can enable more robust and adaptable food systems to be better equipped to handle disruptions such as supply chain challenges or extreme weather events), and so on.

[0048] Additional Example

[0049] One example of the present disclosure includes a method for controlling one or more environmental parameters of a food storage area of a facility. The method may include capturing video of the food storage area of the facility using a video camera, and at the video camera: identifying food items in the captured video of the food storage area; identifying one or more ideal food storage environmental parameters for the identified food items; and transmitting the identified one or more ideal food storage environmental parameters from the video camera to an environmental control system of the facility serving the food storage area. The method may further include controlling the environmental control system of the facility based on the one or more ideal food storage environmental parameters transmitted by the video camera to the environmental control system.

[0050] As an alternative or addition to any of the above examples, in another example, the one or more ideal food storage environmental parameters for the identified food items may include one of a temperature setpoint and a relative humidity setpoint for the environmental control system.

[0051] As an alternative or addition to any of the above examples, in another example, the one or more ideal food storage environmental parameters for the identified food items may include a temperature setpoint and a relative humidity setpoint for the environmental control system.

[0052] As an alternative or addition to any of the above examples, in another example, the environmental control system may include an HVAC system and / or a refrigeration system of the facility serving the food storage area of the facility.

[0053] As an alternative or addition to any of the above examples, in another example, the identified food items may be packaged with barcodes. Identifying the food items may include identifying the barcodes of the food items in the captured video of the food storage area and decoding the barcodes to identify the food items.

[0054] As an alternative or addition to any of the above examples, in another example, the identified food items may include labels with label information. Identifying the food items may include identifying the labels of the food items in the captured video of the food storage area and comparing the label information of the labels with a database of food items to identify the food items.

[0055] As an alternative or addition to any of the above examples, in another example, the identified food items may have shapes. Identifying the food items may include identifying the shapes of the food items in the captured video of the food storage area and comparing the shapes with a database of food item shapes to identify the food items.

[0056] As an alternative or addition to any of the above examples, in another example, the method may further include receiving one or more environmental parameters for the food storage area measured by the video camera.

[0057] In another example, a video camera for a food storage area may include: a camera housing; a camera housed by the camera housing that provides a video stream of the food storage area; and a controller housed by the camera housing and operably coupled to the camera. The controller may be configured to analyze the video stream captured by the camera to identify food items in the food storage area, obtain one or more ideal food storage environment parameters for the identified food items, and transmit the one or more ideal food storage environment parameters to an environmental control system serving the food storage area.

[0058] As an alternative or addition to any of the above examples, in another example, the video camera may further include an RFID scanner housed by the camera housing.

[0059] As an alternative or addition to any of the above examples, in another example, the one or more ideal food storage environment parameters for the identified food items may include one of a temperature setpoint and a relative humidity setpoint for the environmental control system.

[0060] As an alternative or addition to any of the above examples, in another example, the controller may be configured to analyze the video stream captured by the camera to identify the amount of space occupied by food items in the food storage area.

[0061] As an alternative or addition to any of the above examples, in another example, the controller may be configured to analyze the video stream captured by the camera to identify the amount of unoccupied space in the food storage area.

[0062] As an alternative or addition to any of the above examples, in another example, the controller may include a database that identifies one or more ideal food storage environment parameters for each of a plurality of food items.

[0063] As an alternative or addition to any of the above examples, in another example, the controller may include an artificial intelligence engine that is trained to analyze the video stream captured by the camera and identify each of a plurality of different food items including the identified food item.

[0064] As an alternative or addition to any of the above examples, in another example, the controller may be configured to analyze the video stream to identify the shape of the food item, a label present on the food item, and / or a barcode present on the food item, and compare the shape, label, and / or barcode with a food database stored in the memory of the controller to identify the food item in the food storage area.

[0065] In another example, a video-based system for controlling one or more environmental parameters of a food storage area of a facility may include a video camera and an environmental control system serving the food storage area of the facility. The video camera may include a camera housing, a camera housed by the camera housing for providing a video stream of the food storage area, a communication port for communicating with the environmental control system, and a controller housed by the camera housing and operably coupled to the camera and the communication port. The controller may be configured to analyze the video stream captured by the camera to identify food items in the food storage area, identify one or more ideal food storage environmental parameters for the identified food items, and transmit the one or more ideal food storage environmental parameters for the identified food items to the environmental control system via the communication port.

[0066] As an alternative or addition to any of the above examples, in another example, the environmental control system may include an HVAC system and / or a refrigeration system serving the food storage area of the facility.

[0067] As an alternative or addition to any of the above examples, in another example, the environmental control system may be configured to control one or more environmental parameters in the food storage area based on the one or more ideal food storage environmental parameters transmitted by the controller of the video camera.

[0068] As an alternative or addition to any of the above examples, in another example, the controller of the video camera may include an artificial intelligence engine that is trained to analyze the video stream captured by the camera and identify each food item among a plurality of different food items including the identified food item.

[0069] Although several illustrative embodiments of the present disclosure have been described as such, those skilled in the art will readily appreciate that other embodiments can be made and used within the scope of the appended claims herein. However, it should be understood that the present disclosure is illustrative in many respects. Changes can be made to the details, especially those related to the shape, size, arrangement of parts, and exclusion and order of steps, without departing from the scope of the present disclosure. Of course, the scope of the present disclosure is defined in the language of the appended claims.

Claims

1. A method for controlling one or more environmental parameters of a food storage area of a facility, the method comprising: Capturing video of the food storage area of the facility using a video camera; At the video camera: Identifying food products in the captured video of the food storage area; Identifying one or more ideal food storage environmental parameters for the identified food products; and transmitting the identified one or more ideal food storage environmental parameters from the video camera to an environmental control system of the facility serving the food storage area; And Controlling the environmental control system of the facility based on the one or more ideal food storage environmental parameters transmitted by the video camera to the environmental control system.

2. The method according to claim 1, wherein the one or more ideal food storage environmental parameters for the identified food products include one of a temperature setpoint and a relative humidity setpoint for the environmental control system.

3. The method according to claim 1, wherein the environmental control system includes an HVAC system and / or a refrigeration system of the facility serving the food storage area of the facility.

4. The method according to claim 1, wherein the identified food products are packaged with barcodes, and wherein identifying the food products includes identifying the barcodes of the food products in the captured video of the food storage area and decoding the barcodes to identify the food products.

5. The method according to claim 1, wherein the identified food products include tags with tag information, and wherein identifying the food products includes identifying the tags of the food products in the captured video of the food storage area and comparing the tag information of the tags with a database of food products to identify the food products.

6. The method according to claim 1, wherein the identified food products have shapes, and wherein identifying the food products includes identifying the shapes of the food products in the captured video of the food storage area and comparing the shapes with a database of food product shapes to identify the food products.

7. A video camera for a food storage area, the video camera comprising: A camera housing; A camera, which is accommodated by the camera housing and provides a video stream of the food storage area; A controller, which is accommodated by the camera housing and operably coupled to the camera, the controller being configured to: Analyze the video stream captured by the camera to identify food products in the food storage area; Obtain one or more ideal food storage environmental parameters for the identified food products; And Transmit the one or more ideal food storage environmental parameters to an environmental control system serving the food storage area.

8. The video camera according to claim 7, further comprising an RFID scanner accommodated by the camera housing.

9. The video camera according to claim 7, wherein the controller includes an artificial intelligence engine that is trained to analyze the video stream captured by the camera and identify each of a plurality of different food products including the identified food products.

10. The video camera according to claim 7, wherein the controller is configured to analyze the video stream to identify the shape of the food, the label present on the food, and / or the barcode present on the food, and compare the shape, the label, and / or the barcode with a food database stored in the memory of the controller to identify the food in the food storage area.

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