The Power of Ai In Addressing The Challenges Faced By Indian Farmers In The Agriculture Sector: An Analysis
Authors: Ms. Pooja B. Gandhi, Dr. Ashishkumar Parejiya  
Published: December 2023

Over half of Indians find gainful employment in agriculture, and this industry also makes a sizable contribution to the country's GDP. However, Indian farmers face several challenges that hinder their productivity and profitability, including low productivity and yield, dependence on monsoon rains, soil degradation, and nutrient depletion. Additionally, farmers in India face infrastructural and logistical challenges, market volatility, and limited access to credit and technology.
In recent years, computer science has emerged as a crucial field that can help address some of the challenges facing Indian agriculture. This paper aims to explore the role of computer science in Indian agriculture, with a focus on precision farming and IoT-based solutions, the use of AI and machine learning in crop prediction and yield optimization, and the applications of data analytics in crop monitoring and disease detection.
The paper begins with an overview of Indian agriculture and its challenges, providing a background and context for the problem. It then outlines the research questions and objectives, the study's objectives, as well as its scope and limits.
The agricultural difficulties experienced by Indian farmers are the subject of the paper's second section. The section highlights low productivity and yield, dependence on monsoon rains, soil degradation and nutrient depletion, lack of access to credit and technology, market volatility, and infrastructural and logistical challenges. The section discusses the extent of these challenges and their impact on Indian agriculture.
The following section of the paper focuses on the role of computer science in agriculture. It provides an overview of computer science applications in agriculture, including precision farming and IoT-based solutions, the use of AI and machine learning in crop prediction and yield optimization, and the applications of data analytics in crop monitoring and disease detection. The section highlights the potential benefits of these applications in Indian agriculture and discusses the opportunities for innovation and collaboration in this area.
The paper then discusses the existing solutions and their limitations. The section presents an overview of existing solutions and interventions, including success stories and case studies. It also discusses the limitations and challenges of existing solutions, as well as policy and regulatory challenges in technology adoption in agriculture.
The following section focuses on emerging technologies and their potential for Indian agriculture. It provides an overview of emerging technologies in agriculture, including case studies of successful implementation in India. This section covers the role of the government and the private sector in encouraging the use of emerging technology in Indian agriculture, highlighting the potential benefits and problems of doing so.
The report then moves on to discuss data-driven strategies for Indian agriculture. This section explores the ways in which data analytics have been put to use in Indian agriculture, the opportunities for innovation and collaboration that have arisen as a result, and the limitations of data-driven techniques.
The paper then discusses the role of digital platforms in connecting farmers to markets. It provides an overview of digital platforms in agribusiness, including case studies of successful digital platforms in India. The section discusses the potential benefits and challenges of digital platforms for Indian farmers and highlights the role of government and the private sector in promoting the adoption of digital platforms in agriculture.
Finally, the paper concludes with a summary of the key findings and implications of the study. The section emphasizes the potential of computer science in addressing the challenges facing Indian agriculture and the need for policymakers, researchers, and practitioners to collaborate to promote its adoption. The paper concludes with recommendations for future research in this area.