Description:FIELD OF THE INVENTION
This invention relates to Sensor System for Monitoring Quality, Freshness, and Contamination Levels in Crops and Storage Facilities
BACKGROUND OF THE INVENTION
The present invention relates to a sensor-based monitoring system for agricultural crops and storage facilities, enabling real-time assessment of quality, freshness, and contamination levels to ensure food safety and optimal storage conditions.
Agricultural products are prone to degradation due to environmental factors such as temperature, humidity, gas concentration, and microbial contamination. Current monitoring techniques rely on periodic manual testing, which is inefficient and often fails to detect issues before they become critical. There is a need for an automated, real-time sensor system that can provide continuous monitoring of crops from harvest to storage.
Currently, the agricultural industry employs a combination of traditional and advanced technologies to monitor crop quality and storage conditions:
Visual Inspections
Chemical Testing
Environmental Monitoring
Existing technologies have certain limitations:
Reactivity: Many methods detect issues only after they have become apparent, rather than predicting or preventing them.
Destructiveness: Some testing methods require the destruction of samples, leading to waste.
SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention.
This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
The sensor system comprises a network of IoT-enabled devices that collect, transmit, and analyze data from various points within a storage facility or during transit. The sensors can be embedded within packaging, placed in storage units, or installed in transport vehicles.
Gas Sensors: These sensors continuously measure the concentration of gases released by produce during ripening or spoilage. Elevated ethylene levels, for example, indicate over-ripening, while ammonia and sulfur compounds suggest microbial contamination.
Humidity and Temperature Sensors: These sensors help maintain ideal storage conditions by adjusting refrigeration settings based on real-time readings.
Microbial Sensors: Using biosensors and molecular detection techniques, the system can identify pathogens such as E. coli, Salmonella, and molds that pose health risks.
Optical Sensors: Utilizing infrared and ultraviolet spectroscopy, these sensors analyze changes in color and reflectance patterns to detect ripening stages, bruising, or contamination.
Wireless Communication Module: Data from the sensors is transmitted via Wi-Fi, Bluetooth, or LoRaWAN to a central cloud platform.
Machine Learning-Based Analytics: The collected data is processed using machine learning algorithms to identify patterns, predict spoilage risks, and recommend actions such as modifying storage conditions or segregating contaminated products.
BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein:
FIGURE 1: SYSTEM ARCHITECTURE
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a",” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and/or “including,” when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In addition, the descriptions of "first", "second", “third”, and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The sensor system comprises a network of IoT-enabled devices that collect, transmit, and analyze data from various points within a storage facility or during transit. The sensors can be embedded within packaging, placed in storage units, or installed in transport vehicles.
Gas Sensors: These sensors continuously measure the concentration of gases released by produce during ripening or spoilage. Elevated ethylene levels, for example, indicate over-ripening, while ammonia and sulfur compounds suggest microbial contamination.
Humidity and Temperature Sensors: These sensors help maintain ideal storage conditions by adjusting refrigeration settings based on real-time readings.
Microbial Sensors: Using biosensors and molecular detection techniques, the system can identify pathogens such as E. coli, Salmonella, and molds that pose health risks.
Optical Sensors: Utilizing infrared and ultraviolet spectroscopy, these sensors analyze changes in color and reflectance patterns to detect ripening stages, bruising, or contamination.
Wireless Communication Module: Data from the sensors is transmitted via Wi-Fi, Bluetooth, or LoRaWAN to a central cloud platform.
Machine Learning-Based Analytics: The collected data is processed using machine learning algorithms to identify patterns, predict spoilage risks, and recommend actions such as modifying storage conditions or segregating contaminated products.
NOVELTY:
The advancements in sensor technologies aimed at enhancing the monitoring and management of crop quality, freshness, and contamination levels in agricultural and storage settings.
, Claims:1. A sensor-based monitoring system for tracking quality, freshness, and contamination in crops and storage facilities, comprising:
• A plurality of gas sensors to detect spoilage-indicating compounds;
• Humidity and temperature sensors to maintain optimal storage conditions;
• Microbial sensors for detecting harmful pathogens;
• Optical sensors for non-invasive freshness analysis;
• A wireless communication module for real-time data transmission;
• A machine learning-based analytics module for predictive analysis and decision-making.
2 The system of claim 1, wherein the gas sensors measure ethylene, carbon dioxide, ammonia, and sulfur compounds to determine spoilage levels.
3. The system of claim 1, wherein the microbial sensors use biosensing technology to detect bacteria and fungal contamination.
4. The system of claim 1, wherein the optical sensors employ spectroscopy techniques to assess ripeness, bruising, and contamination.
5. The system of claim 1, wherein the wireless communication module transmits data to a cloud-based platform for remote monitoring and alerts.
6. The system of claim 1, wherein the machine learning-based analytics module processes sensor data to predict spoilage trends and suggest corrective actions.