Description:[001] The present invention relates to the field of precision agriculture and smart farming technologies. More particularly, it pertains to systems and methods that utilize artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), edge computing, and blockchain to enable data-driven, automated, and adaptive agricultural practices. The invention is specifically directed toward improving the climate resilience of crops by dynamically responding to environmental conditions and optimizing resource usage such as water, fertilizers, and energy. By integrating real-time data collection, intelligent analytics, and secure information sharing, the invention offers a holistic approach to sustainable agriculture aimed at enhancing productivity, minimizing ecological impact, and securing food systems in the face of climate variability and change.
BACKGROUND OF THE INVENTION
[002] Agriculture remains one of the most climate-sensitive sectors globally, with crop yields increasingly affected by erratic weather patterns, rising temperatures, prolonged droughts, and unexpected flooding events. These climate-induced stressors pose significant challenges to food security, farmer livelihoods, and the sustainability of traditional agricultural practices. Conventional farming techniques often rely on fixed schedules for irrigation, fertilization, and pest control, which do not account for the dynamic and localized environmental conditions experienced on the ground. Consequently, such static methods contribute to resource inefficiencies, overuse of inputs, soil degradation, and greenhouse gas emissions.
[003] In recent years, the concept of precision agriculture has emerged as a technological response to optimize agricultural inputs and maximize crop outputs through site-specific management. While this approach has shown promise, its full potential remains underutilized due to limitations in real-time decision-making, interoperability of systems, and data integration across different farming components. Moreover, many existing solutions are fragmented, lacking a unified platform that can synthesize and interpret diverse data streams in the context of changing climatic conditions.
[004] The integration of artificial intelligence (AI) and machine learning (ML) into precision agriculture offers the capability to transform how agricultural decisions are made. AI models can analyze vast amounts of data from farm sensors, satellite imagery, weather forecasts, and historical records to generate actionable insights tailored to specific crops, geographies, and climatic trends. However, challenges persist in terms of latency, connectivity in remote farming areas, data security, and trust among stakeholders.
[005] Emerging technologies such as edge computing and blockchain provide promising solutions to these challenges. Edge computing enables local, real-time data processing at the farm level, reducing dependence on constant cloud connectivity. Blockchain technology ensures data transparency, integrity, and traceability, thereby enhancing trust among farmers, agronomists, insurers, and policymakers.
[006] Despite these technological advancements, there remains a pressing need for an integrated system that combines AI, IoT, edge computing, and blockchain into a unified framework capable of improving crop resilience under climate stress. Such a system must not only process data intelligently but also support decentralized decision-making and enable secure, collaborative agricultural ecosystems. The present invention addresses this critical need by introducing a novel platform that leverages the synergy of advanced digital technologies to empower farmers with real-time, climate-smart agricultural practices.
SUMMARY OF THE INVENTION
[007] The present invention provides an integrated, intelligent agricultural system that leverages advanced technologies—namely artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), edge computing, and blockchain—to enable precision agriculture aimed at enhancing climate resilience in crops. The system is designed to collect, analyze, and act upon real-time environmental and crop-specific data to inform dynamic farming decisions. It addresses the growing need for climate-adaptive agriculture by empowering farmers with tools that deliver actionable insights and automate resource management processes, thereby reducing input costs and maximizing yield even under unpredictable climatic conditions.
[008] At the core of the system is a network of IoT-enabled sensors deployed across agricultural fields, capturing a wide array of data points including soil moisture, pH levels, ambient temperature, humidity, light intensity, and real-time crop imagery. This data is initially processed at the edge using localized computing devices, allowing for rapid response actions—such as triggering automated irrigation—without relying solely on cloud connectivity. The edge computing layer ensures minimal latency and continued operation in remote or connectivity-constrained environments, making the invention highly adaptable to diverse geographical locations.
[009] The processed data is then transmitted to a centralized cloud-based AI engine that uses predictive analytics and machine learning models to generate customized recommendations for farming operations. These models are trained on a combination of historical agricultural datasets, regional climate trends, and real-time sensor data. Based on this analysis, the system provides recommendations on optimal planting dates, irrigation schedules, fertilizer dosages, pest and disease control strategies, and harvesting periods. These recommendations are dynamically updated as new data is received, allowing the system to adapt to changing environmental conditions and crop development stages.
[010] To ensure the security, integrity, and traceability of all data and recommendations generated by the system, a blockchain-based ledger is integrated into the platform. This distributed ledger maintains an immutable record of sensor data, AI-driven decisions, and actions taken on the farm. It also facilitates transparent and secure sharing of information among multiple stakeholders, including farmers, agricultural advisors, government agencies, insurance companies, and supply chain partners. Furthermore, smart contracts on the blockchain enable automation of transactions such as crop insurance claims, subsidy disbursements, and carbon credit verification, thereby reducing administrative overhead and enhancing trust in the agricultural ecosystem.
[011] The user interacts with the system through a multilingual, user-friendly mobile or web application interface that translates complex AI-driven insights into simple, actionable advice. The platform is designed to be inclusive, ensuring accessibility for farmers with varying levels of digital literacy. By offering an end-to-end solution—from real-time data acquisition and intelligent analysis to secure data sharing and action guidance—the invention revolutionizes modern agriculture. It equips farmers with the tools they need to sustainably increase productivity, reduce environmental impact, and build long-term resilience against the uncertainties of climate change.
DESCRIPTION OF THE DRAWINGS
[012] The accompanying figures included herein, and which form parts of the present invention, illustrate embodiments of the present invention, and work together with the present invention to illustrate the principles of the invention Figures:
[013] Fig. 1: A schematic diagram illustrating the overall architecture of the AI-powered precision agriculture system, including IoT sensors deployed in the field, edge computing units, cloud-based AI engine, blockchain ledger, and the user interface for real-time decision support.
[014] Fig. 2: A flowchart depicting the end-to-end data processing and decision-making workflow, beginning with data collection from field sensors, followed by edge and cloud-based analysis, blockchain logging, and culminating in the delivery of actionable recommendations to the user interface.
DETAILED DESCRIPTION OF THE INVENTION
[015] The present invention provides a comprehensive, AI-powered precision agriculture system that integrates real-time environmental monitoring, data analytics, decentralized decision-making, and secure data sharing to enhance crop resilience against climate variability. The invention is composed of five key modules: (1) IoT Sensor Network, (2) Edge Computing Layer, (3) Cloud-Based AI Engine, (4) Blockchain Data Layer, and (5) User Interface and Decision Support System. Each module is described in detail below.
IoT Sensor Network
[016] The system includes a distributed network of IoT (Internet of Things) sensors strategically deployed throughout agricultural fields. These sensors continuously monitor critical parameters such as soil moisture, pH levels, temperature, humidity, atmospheric pressure, rainfall, light intensity, and crop health using multispectral imaging. The sensors are solar-powered and capable of wireless data transmission, ensuring uninterrupted operation even in remote farming locations. Data is collected at high frequency and transmitted in real-time to local edge devices for pre-processing. The sensor data forms the foundation of the decision-making process, enabling hyper-localized insights into crop and environmental conditions.
Edge Computing Layer
[017] The edge computing component serves as the first level of analysis. It receives raw data from the IoT sensors and performs immediate preprocessing tasks such as filtering, noise reduction, normalization, and threshold-based anomaly detection. Basic rule-based alerts (e.g., irrigation trigger when soil moisture falls below a defined threshold) can be executed directly at the edge level to reduce latency and bandwidth usage. This decentralized processing model ensures the system remains functional in low-connectivity areas and improves the response time for time-sensitive agricultural operations.
Cloud-Based AI Engine
[018] After edge-level processing, the cleaned and structured data is transmitted to a centralized cloud-based AI engine. This engine houses multiple machine learning and deep learning models trained on vast datasets, including historical climate data, soil characteristics, crop phenology, and regional agronomic practices. The engine performs advanced analytics such as weather-aware crop modeling for predicting disease outbreaks or water stress, yield forecasting using convolutional neural networks (CNNs) and time-series analysis, and resource optimization models to recommend precise irrigation, fertilization, and pest control schedules. These AI models continuously evolve through reinforcement learning and real-time feedback from sensor outcomes and user actions, thereby improving the system’s predictive accuracy and contextual relevance over time.
Blockchain Data Layer
[019] To ensure data integrity, transparency, and secure collaboration among stakeholders, the invention includes a blockchain-based data management layer. All environmental readings, AI-generated recommendations, and user-executed actions are cryptographically recorded on a distributed ledger. This immutable record facilitates traceability and accountability. Smart contracts deployed on the blockchain automate various transactions such as issuance of crop insurance payouts based on weather anomalies and damage data, disbursement of subsidies for adopting sustainable practices, and verification of carbon sequestration metrics for carbon credit trading. This secure infrastructure encourages greater trust and collaboration between farmers, agronomists, insurers, policymakers, and supply chain actors.
User Interface and Decision Support System
[020] The user interacts with the system through a mobile or web-based application that delivers personalized, actionable insights in an intuitive format. The interface supports multilingual capabilities and visualizations, making it accessible to users regardless of digital literacy level. The app provides real-time alerts and recommendations, interactive dashboards showing soil and crop conditions, historical data trends and forecasted insights, and tutorials and guidance for sustainable farming practices. The user interface acts as a bridge between complex AI outputs and practical on-field implementation, ensuring farmers can easily understand and act on system recommendations.
[021] The combination of real-time sensing, intelligent analytics, decentralized execution, and secure data management creates a holistic platform for climate-resilient agriculture. The invention allows farmers to reduce wasteful input use, respond promptly to environmental stressors, improve crop yield and quality, and gain access to financial incentives through transparent data records. By enabling precision farming that adapts dynamically to environmental and crop conditions, this invention sets a new standard for sustainable agriculture in the face of climate change.
[022] The present invention introduces a transformative approach to agriculture by integrating cutting-edge technologies such as artificial intelligence, machine learning, Internet of Things, edge computing, and blockchain into a unified platform. This intelligent precision agriculture system offers a dynamic, real-time, and adaptive solution to the challenges posed by climate variability, resource inefficiency, and food insecurity. By leveraging data-driven insights, the system enables optimized farming practices, enhances crop resilience, and supports sustainable land management. Its ability to process vast environmental and agronomic data ensures that farmers receive timely, accurate, and localized recommendations tailored to specific crop and regional needs.
[023] The invention holds immense potential for future development and expansion. With the ongoing evolution of AI algorithms, the platform can be enhanced to include more complex predictive models for multi-crop systems, intercropping dynamics, and early detection of new pests and diseases. Integration with satellite remote sensing and drone-based imagery can further refine monitoring and yield estimation accuracy.
[024] Additionally, the platform can be scaled to support regional and national-level agricultural planning by aggregating anonymized data for macro-level insights. Collaborations with governmental bodies, climate research organizations, and agri-tech startups can facilitate the development of open data standards and foster innovation. In the long term, the system can also be adapted to support climate-smart urban agriculture, greenhouse management, and vertical farming systems, contributing to resilient food systems worldwide.
[025] This invention represents a significant advancement in the field of agricultural automation and sustainability. It bridges the gap between traditional farming and modern digital agriculture by offering a scalable, accessible, and inclusive platform. The seamless coordination between sensor-based monitoring, intelligent analytics, and secure data management creates a reliable ecosystem that empowers stakeholders at every level—from smallholder farmers to government agencies. Moreover, the use of blockchain provides a high level of trust and transparency, which is crucial for collaborative agriculture and policy-driven support mechanisms. Overall, this system not only addresses current agricultural challenges but also establishes a robust foundation for long-term food and environmental security.
, Claims:1. A system for AI-powered precision agriculture for climate-resilient crops, comprising a network of Internet of Things (IoT) sensors configured to monitor environmental and crop-specific parameters including soil moisture, pH, temperature, humidity, rainfall, and crop health, and to transmit real-time data to a processing unit.
2. The system of claim 1, wherein the IoT sensor data is processed locally using edge computing devices configured to perform data preprocessing operations including filtering, normalization, anomaly detection, and rule-based automation for real-time decision-making.
3. The system of claim 2, wherein the edge computing devices are further configured to trigger automated agricultural operations such as irrigation, fertilization, or pest control based on predefined thresholds or AI-driven recommendations.
4. The system of claim 1, wherein the sensor data is transmitted to a cloud-based artificial intelligence engine comprising machine learning models trained to analyze historical, environmental, and real-time data to generate context-specific agricultural recommendations.
5. The system of claim 4, wherein the AI engine includes predictive models configured to perform crop yield forecasting, disease and pest outbreak prediction, irrigation scheduling, and nutrient optimization based on localized climatic and agronomic conditions.
6. The system of claim 1, further comprising a blockchain-based data layer configured to store sensor data, AI-generated decisions, and farming activities in a secure, immutable, and distributed ledger to ensure data integrity, traceability, and transparency.
7. The system of claim 6, wherein smart contracts deployed on the blockchain are configured to automate agricultural transactions including crop insurance payouts, subsidy disbursements, and carbon credit verifications based on real-time sensor and system data.
8. The system of claim 1, further comprising a user interface accessible via mobile or web application, the interface being configured to provide real-time alerts, data visualizations, historical trends, and personalized farming recommendations in a multilingual and user-friendly format.
9. The system of claim 8, wherein the user interface is further configured to receive feedback from the user, enabling adaptive learning and continuous improvement of AI model performance based on real-world outcomes.
10. The system of claim 1, wherein the integration of IoT sensors, edge computing, AI analytics, blockchain security, and user interface forms a unified platform that enables sustainable, climate-resilient agriculture through real-time, data-driven decision support.