Internet-of-things based agricultural assistance system integrated with hyperspectral imaging for analysis of agricultural land using hyperspectral analysis, has capturing unit for capturing images to collect images comprising red green and blue pixel values
	SHARMA N
	2025-03-26
专利权人	UNIV MOTHERHOOD (UYMO-Non-standard)
申请日期	2025-03-26
专利号	IN202511028607-A
成果简介	NOVELTY - The system has a capturing unit for capturing the images to collect the images comprising red, green and blue (RGB) pixel values. A data processing unit extracts spectral information indicative of soil properties comprising moisture, electrical conductivity, power of hydrogen (pH), ultraviolet radiation, temperature and nutrient levels e.g. nitrogen, phosphorus, and potassium and crop health indicators. A wireless communication protocol and a user-friendly web interface enable data-driven decision-making for optimizing land management and enhancing crop yields. The processed data is transmitted in real time via wireless communication protocols to a centralized server. The hyperspectral images of agricultural land are captured using an ESP32S3 module integrated with Hyper Intellistack. The wireless communication protocol is Wireless Fidelity (Wi-Fi), global systems for mobile communication (GSM) or Long Range(LoRa). USE - Internet of Things (IoT) based agricultural assistance system integrated with hyperspectral imaging for analysis of agricultural land using hyperspectral analysis. Can also be used for monitoring crop health and soil quality e.g. manual inspections and multispectral imaging. ADVANTAGE - The system empowers farmers and stakeholders to make data-driven decisions and optimize land management and farmers and agricultural managers to optimize irrigation, fertilization and pest control strategies, enhances overall operational efficiency in agricultural practices, prediction accuracy, various types of agriculture and research operations using hyperspectral technology, agricultural productivity, sustainable land use, productivity ultimately and crop yields through precise and rapid analysis enabled by hyperspectral technology and Hyper Intellistack, promotes sustainable land use, farmers to adopt precise agricultural practices for improved crop production, sustainability, and resource management, early detection of issues e.g. disease, water stress, and pest infestations and real-time detection of crop stress, soil degradation, and nutrient deficits, allows farmers to monitor fields in real time, timely interventions and detection of subtle variations in soil and crop reflectance correlated with specific properties e.g. moisture and nutrients, extracts RGB pixel values for intuitive visualization or fused with hyperspectral data to enhance model accuracy, ensures quicker and accurate results, accuracy and farmer trust, provides users with personalized, data-driven insights into soil health, moisture levels, and nutrient content and long-term insights into soil health and crop performance, avoids complexity and cost barriers, supports optimized irrigation, fertilization, and pest management, classifies reflectance data accurately using a machine-learned model into groupings, determines whether to treat the canopy for aphids ultimately, offers high precision, non-destructive analysis and fast and solvent-free detection without environmental pollution, ensures that stakeholders e.g. farmers or agricultural managers, accesses comprehensive dashboards and analytics which support informed decision-making related to irrigation, fertilization, crop selection and overall land management, achieves cost-effective automation, reduces reliance on manual labor and delays typical of traditional soil testing method and helps farmers optimize irrigation, fertilization, and crop selection and boosting productivity while promoting sustainable farming practices and resource management.
IPC 分类号	G01N-021/17 ; G01N-021/31 ; G01N-033/24 ; G06Q-050/02 ; G06V-020/10
国家	印度
专业领域	信息技术
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/13498
专题	中国科学院新疆生态与地理研究所
作者单位	UNIV MOTHERHOOD (UYMO-Non-standard)
推荐引用方式 GB/T 7714	SHARMA N. Internet-of-things based agricultural assistance system integrated with hyperspectral imaging for analysis of agricultural land using hyperspectral analysis, has capturing unit for capturing images to collect images comprising red green and blue pixel values. IN202511028607-A[P]. 2025.

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