Predictive Analytics in Smart Farming – A Case Study for Tamil Nadu

Abstract

This thesis delves into the transformative potential of predictive analytics in smart farming, offering a thorough examination of cutting-edge technological solutions aimed at overcoming modern agricultural challenges. It begins by tracing the evolution of farming practices, from traditional methods rooted in experience to the present-day integration of technology-driven approaches. The study explores how innovations such as Artificial Intelligence (AI), the Internet of Things (IoT), Big Data, sensors, drones, and mobile internet are revolutionizing smart farming, enabling efficient data collection, storage, analysis, and decision-making to enhance agricultural productivity.
Focusing on Tamil Nadu, India, the research highlights the region’s agricultural landscape, which faces significant challenges due to climate change, unpredictable rainfall, water mismanagement, and inefficient crop rotation. Traditional farming, heavily reliant on historical knowledge and experiential decision-making, struggles to mitigate these issues. By incorporating predictive analytics, automation, and data-driven farming techniques, this study investigates how technology can optimize water resource management and improve overall crop yield.
The findings reveal a steady rise in seasonal temperatures from 2020 to 2024, emphasizing the growing impact of climate change on agriculture. Additionally, an analysis of rainfall patterns from 2008 to 2022 shows significant variability, with some years experiencing excessive rainfall and others severe drought, leading to fluctuations in crop production. Key crops in Tamil Nadu—including paddy, cholam, cumbu, ragi, pulses, and oilseeds—are particularly affected by these climatic shifts and irrigation challenges.
By integrating predictive analytics and advanced farming technologies, this research provides valuable insights into mitigating climate-related risks, improving water management, and promoting sustainable agricultural practices. The study offers practical recommendations for policymakers, researchers, and farmers to adopt smart farming methods, fostering a more resilient and efficient agricultural ecosystem in the face of climate change.