REVOLUTIONIZING FARMING PRACTICES: ECONOMIC AND PRACTICAL INSIGHTS INTO DRONE-ASSISTED AGRICULTURE

Indian agriculture, the backbone of the nation’s economy, contributes significantly to GDP, provides employment to nearly half the population, and ensures food security for over 1.4 billion people. However, the sector faces challenges like declining productivity, limited mechanization, labor shortages, and climate change impacts. Traditional farming methods, particularly in paddy cultivation, often hinder scalability and efficiency. Drones, or unmanned aerial vehicles (UAVs), offer a transformative solution. Equipped with advanced sensors and imaging capabilities, drones provide real-time data on crop health, soil conditions, and pest infestations. This enables farmers to make precise, data-driven decisions, optimizing inputs like water, fertilizers, and pesticides. Such efficiencies are crucial for India’s smallholder farmers, who operate under tight economic constraints. A study in Tamil Nadu focusing on paddy farming revealed that drone-assisted agriculture improves economic efficiency by 90%. This is achieved through precise monitoring and targeted interventions, reducing resource wastage. For example, drones pinpoint specific areas needing attention, allowing selective application of inputs instead of uniform distribution. Cultivation costs decrease by approximately 30%, thanks to reduced labor and input inefficiencies. Most importantly, the study found a 41% increase in farmer income, driven by higher yields and better-quality produce. Timely interventions and optimal resource management ensure healthier crops, minimizing losses from pests and diseases and enhancing farm productivity. Despite these benefits, drone adoption in Indian agriculture faces hurdles such as high initial costs, limited technical expertise, and regulatory challenges. Addressing these issues through subsidies, policy support, and farmer training programs is essential to maximize the technology's potential and promote sustainable agricultural practices. By leveraging drones, Indian agriculture can overcome critical challenges, ensuring improved productivity, profitability, and sustainability for farmers.

Weeds cause significant yield and economic losses by competing with crops and increasing production costs. Compounding these challenges are labor shortages, herbicide resistance, and environmental pollution, making weed management increasingly difficult. In response, precision weed control (PWC) technologies, such as robots and unmanned aerial vehicles (UAVs), have emerged as innovative solutions. These tools offer farmers high precision (±1 cm spatial accuracy), enabling efficient and sustainable weed management. Herbicide spraying robots, mechanical weeding robots, and laser-based weeders are deployed on large-scale farms in developed countries. Similarly, UAVs are gaining popularity in many countries, particularly in Asia, for weed monitoring and herbicide application. Despite advancements in robotic and UAV weed control, their large-scale adoption remains limited. The reasons for this slow uptake and the barriers to widespread implementation are not fully understood. To address this knowledge gap, our review analyzes 155 articles and provides a comprehensive understanding of PWC challenges and needed interventions for scaling. This review revealed that AI-driven weed mapping in robots and UAVs struggles with data (quality, diversity, bias) and technical (computation, deployment, cost) barriers. Improved data (collection, processing, synthesis, bias mitigation) and efficient, affordable technology (edge/hybrid computing, lightweight algorithms, centralized computing resources, energy-efficient hardware) are required to improve AI-driven weed mapping adoption. Specifically, robotic weed control adoption is hindered by challenges in weed recognition, navigation complexity, limited battery life, data management (connectivity), fragmented farms, high costs, and limited digital literacy. Scaling requires advancements in weed detection and energy efficiency, development of affordable robots with shared service models, enhanced farmer training, improved rural connectivity, and precise engineering solutions. Similarly, UAV adoption in agriculture faces hurdles such as regulations (permits), limited payload and battery life, weather dependency, spray drift, sensor accuracy, lack of skilled operators, high initial and operational costs, and absence of standardized protocol. Scaling requires financing (subsidies, loans), favorable regulations (streamlined permits, online training), infrastructure development (service providers, hiring centers), technological innovation (interchangeable sensors, multipurpose UAVs), and capacity building (farmer training programs, awareness initiatives).

Digital agriculture predetermines the development of robotic agricultural technologies for the application of pesticides and fertilizers using unmanned aerial systems, which are based on unmanned aerial vehicles (UAVs) with a certain working load for monitoring agricultural land and applying agrochemicals. ( Research purpose ) To develop a technology for variable-rate application of pesticides and fertilizers using unmanned aerial vehicles in digital agriculture. ( Materials and methods ) In the process of study, the authors used the methodological recommendations on the application of chemicals in the precision farming system (offered by VIM), as well as the normative and technical documentation for unmanned aircraft systems. ( Results and discussion ) It was shown that the developed technology includes the sequential execution of information and technological operations in off-line and on-line modes. It was found that the application rate of the liquid pesticides of 10-20 liters per hectare reduces losses due to drift from the treatment area and ensures the highest productivity of pesticide application using unmanned aerial vehicles. It was determined that the field processing performance increases as the run length increases, and decreases with the increasing flow rate of the liquid chemical. The rational run length was established to equal 0.8-3.2 kilometers. The authors established requirements for the spraying quality of unmanned aerial vehicles. It was proved that to increase the productivity of unmanned aerial vehicles during plant top-dressing, it is necessary to use unmanned aerial vehicles with a larger working load of 300-400 kilograms. ( Conclusions ) The authors have developed a technology for variable-rate application of pesticides and fertilizers using unmanned aerial vehicles, algorithms for preparing them for flight, monitoring agricultural lands, making a field orthophotomap, electronic maps of vegetation indices, the phytosanitary status of crops, and variable-rate application of pesticides and fertilizers.

Emerging technology like civilian unmanned aerial vehicle (UAV) has the potential to exert an impact on agriculture production and crop damages assessment. Securing sustainability in agriculture requires accountability and responsibility of the actors engaged in the deployment of the civilian UAV due to associated deployment risks and unintended consequences. UAV technology has the potential to replace remote sensing technologies like satellite imageries and piloted aircraft used in the crop insurance business. The governance of deployment of UAV technology in India is a complex challenge when a well-developed regulatory system is not in place and diverse actors involved in the deployment and operation of civilian UAV for agricultural applications. Therefore, two main questions, how UAV innovations can lead to sustainability in Indian agriculture and how are the issues of governance of civil UAV innovations in crop insurance applications addressed, are dealt with. The responsible innovation approach is adopted as a theoretical framework. The exploratory and qualitative study used in-depth interviews, and the interviewees were selected through snowball sampling technique. The results suggest that in the governance of emerging technologies like UAV certain values such as trust, transparency, safety, autonomy, and environmental friendliness assumed high significance. Findings also suggest that UAV has the risk-taking ability in adverse weather condition. The UAV technology also creates values (social, economic and environmental) for deployment in the crop insurance business in India.

In the current era, Indian agriculture faces a significant demand for increased food production, which has led to the integration of advanced technologies to enhance efficiency and productivity. Drones have emerged as transformative tools for enhancing precision agriculture, reducing costs, and improving sustainability. This study provides a comprehensive review of drone adoption in Indian agriculture by examining its effects on precision farming, crop monitoring, and pesticide application. This research evaluates technological advancements, regulatory frameworks, infrastructure, farmers' perceptions, and the financial accessibility of drone technology in the Indian agricultural context. Key findings indicate that, while drone adoption enhances efficiency and sustainability, challenges such as high costs, lack of training, and regulatory barriers hinder widespread implementation. This paper also explores the growing market for agricultural drones in India, highlighting key industry players and projected market growth. Furthermore, it addresses regional differences in adoption rates and emphasizes the increasing social acceptance of drones among Indian farmers. To bridge the gap between potential and practice, the study proposes several policy and institutional recommendations, including government-led financial incentives, training programs, and public-private partnerships to facilitate drone integration. Moreover, this review article also highlights technological advancements, such as AI and IoT, in agriculture. Finally, open issues and future research directions for drones are discussed.

Indian agriculture contributes to the GDP, but our nation still needs to improve productivity and efficiency to the fullest extent possible. Numerous aspects and concerns need to be identified, supported, and equipped with solutions. Now agriculture sector is the fastest-growing sector, which is faced with several issues, one of which is the lack of labour for farming. Some additional issues or challenges are extreme weather conditions, inadequate and ineffective fertilizer application, infection, illnesses, allergies, and other health issues brought on by chemical applications (fungicide, pesticide, insecticide, etc.). Drones, also called Unmanned Aerial Vehicles (UAV), have developed remarkably in recent years. Common applications of drones are Pesticide application, soil sampling and fertilizing, farm animal observation, real-time aerial imagery, sensor data collection, etc. These drones have been primarily created to speed up, boost productivity, and effectively utilize agricultural resources. The government is working toward a liberalized policy to encourage drones and also provide institutions, individual farmers, and businesses with significant financial incentives to buy and utilize or build drones. If farmers start to trust drones for spray-related tasks, there's a strong chance their use will be expanded to other revolutionary use cases as well, which will be beneficial for Indian agriculture.

Technological advances can significantly transform agrarian rural areas by increasing productivity and efficiency while reducing labour intensive processes. For instance, the usage of Unmanned Aerial Vehicles (UAVs) can offer flexibility collecting real-time information of the crops enabling farmers to take timely decisions. However, little is known about the barriers to the adoption of such technologies by rural farmers in emerging economies like India. Building on an extensive literature review, focussed group discussions, and field visits, the barriers impacting the adoption are identified and classified into technical, social, behavioural, operational, economic, and implementation categories. The relevance of each barrier and its importance is evaluated using a hybrid multi-criteria framework built on the theory of Fuzzy Delphi and Fuzzy Analytical Hierarchy Process to identify the most crucial barriers to the adoption of UAVs to implement precision agriculture in rural India. The paper suggests new avenues for accelerating technology adoption in rural areas of emerging economies.

Digital agricultural production is based on robotic agricultural technologies for the use of pesticides and fertilizers using unmanned aerial systems, which are based on unmanned aerial vehicles for monitoring agricultural land, the pesticides application, fertilizers and other agrochemicals. (Research purpose) To develop an unmanned helicopter based aircraft for applying pesticides and fertilizers, and to substantiate its technological parameters. (Materials and methods) The authors used methodological recommendations on the use of chemicals in the precision farming system, regulatory and technical documentation for unmanned aircraft systems. (Results and discussion) The authors determined the unmanned aerial vehicle main flight technical and technological parameters for the implementation of the applying pesticides and fertilizers process. They established the dependences of its productivity on the norms of introducing working fluids of pesticides and fertilizers, the agricultural field length, and the approach distance to the field. (Conclusions) The authors developed a helicopter-type unmanned aerial vehicle of a coaxial design with a take-off mass of 280 kilograms and a payload of 50-80 kilograms, a rotor diameter of 5.3 meters, a constructive boom width with sprayers of 5 meters, a working flight height of 1-5 meters, a working speed of 40-60 kilometers per hour, the rate of working fluid of pesticides application 10-20 liters per hectare and nitrogen fertilizers 30-120 liters per hectare. They established rational values for the application rates of pesticides – 10-20 liters per hectare, the agricultural field length – at least 0.8 kilometers, ensuring maximum productivity in flight hour when processing the agricultural field. They showed that the flight distance minimizing from the runway to the field significantly increased the productivity of applying pesticides and fertilizers.

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.

PurposeThe purpose of this paper is to carry out an empirical investigation of the role of various factors such as economics, social, marketing, cultivation and government in adoption of organic farming. Further, this study examines the factors that influence farmers’ choice of adopting organic farming, based on their demographic classification such as education level, farm size, farming experiences and land ownership of the organic farmers.Design/methodology/approachTo address the research objectives, the primary data were collected with the help of a structured questionnaire from 200 respondents. In this study, the QUAL–QUAN sequence of mixed method design was used. Four focus groups were conducted to identify the factors of organic farming adoption. Further, multinomial regression analysis was applied to analyze the differential impact of these factors in relation to the farmers’ demographic classification.FindingsThe study found five major factors that affect the adoption of organic farming (economic, social, marketing, cultivation, government policy) in India. The study also observed that marketing and government policy factors were most crucial in influencing all types of farmers irrespective of their educational level. The farmers with more farming experience were more concerned about social factors. Similarly, the farmers using lease farms were found to be concerned about the economic viability of organic farming.Social implicationsThis study suggests that without government support, the adoption of organic agriculture seems to be a highly challenging task in a situation, where majority of the farmers fall under the small and marginal category. Hence, to promote organic farming in a developing country like India, the government has to invest more in schemes where farmers should get exclusive training and support to strengthen their intention behind the adoption of the organic farming.Originality/valueBased on the collective insights from the studies, the different stakeholders with interest in organic agriculture may frame necessary strategies to promote organic farming.

It was noted that when forming the configurations of an unmanned aerial system for pesticide and fertilizer application, it is necessary to take into account the interdependence of unmanned and ground-based aerial systems. (Research purpose) To develop the configurations of an unmanned aerial system for pesticide and fertilizer application. (Materials and methods) The authors used Methodological recommendations on the use of chemicals in the precision farming system (VIM), regulatory and technical documentation for unmanned aerial systems. (Results and discussion) The authors developed a flowchart of the algorithm for forming the configurations of a helicopter type unmanned aerial system for fertilizer and pesticide application, including the formation of both unmanned and ground-based aerial systems. The authors calculated the aerodynamic characteristics of an unmanned coaxial rotor aircraft with a take-off weight of 280 kilograms and a payload of 100 kilograms. A modular-designed sprayer was offered. The authors substantiated the structure of the ground-based aerial complex in the form of a mobile transporter-tanker with a basic transport platform, lifting and transporting and refueling modules, and a universal ground control panel for the pilot-operator. (Conclusions) The authors formed reasonable configurations of a helicopter type unmanned aerial system for pesticide and fertilizer differentiated application in the precision farming system. Aircraft performance limitations were identified for the application of fertilizers and pesticides by a helicopter type unmanned aerial vehicle: the payload of at least 100 kilograms, the operating altitude of 1.0-1.5 meters when bypassing the agricultural field topography and avoiding possible obstacles, the operating airspeed kept below 60 kilometers per hour, automatic take-off and landing on a limited area, autoflight at the speed of 60 kilometers per hour at a one meter altitude in a tacking mode. It was showed that the static ceiling margin, without taking the earth influence into account, with a 280-kilogram flight mass, is 1300 meters, which allows flying in mountainous areas, for example, for the treatment of vineyards with pesticides.

Precision farming is a feasible approach for sustainable agriculture. Precision farming makes use of remote sensing to macro-control of GPS to locate precisely ground position and of GIS to store ground information. It precisely establishes various operations, such as the best tillage, application of fertilizer, sowing, irrigation, harvesting etc., and turns traditional extensive production to intensive production according to space variable data. Precision farming not only may utilize fully resources, reduce investment, decrease pollution of the environment and get the most of social and economic efficiency, but also makes farm products, the same as industry, become controllable, and be produced in standards and batches. The use of inputs (fertilizers and pesticides) based on the right quantity, at the right time, and in the right place. This type of management is commonly known as “Site-Specific Management”. The productivity gains in global food supply have increasingly relied on expansion of irrigation schemes over recent decades, with more than a third of the world's food now requiring irrigation for production. However, precision farming has been confined to developed countries. Land tenure system, smaller farm size and crop diversity have limited the scope of precision farming in India. However, there is a wide scope for precision farming in irrigated/ commercial/ fruit and vegetable crops/ high value crops. It is apparent that there is a tremendous scope for precision farming in India as well and it is necessary to develop database of agriculture resources, which will act as decision support system at the farm.

Countries like India, more than 70% of the people depend on rice cultivation. Based on this precision agriculture in India requires the information about the condition of cultivated plants and the response to undesirable appearances of pests. Recent technology, Unmanned Aerial Vehicle (UAV) performs the aerial spraying over rice plants to kill the pests which are harmful. But, offsite and less amount of droplet deposition over the plants is the major concern in pesticide spraying applications. The rotors of the unmanned aerial vehicle effect the deposition of the droplets over the rice plants. This study results on the impact of the UAV rotors speed on the spray deposition and spraying liquid coverage on the plant surface. The sample liquid (water) sprayed from the moving UAV over the sample plant using a flat fan nozzle with 0.2 MPa. The UAV moved with the speed of the 2 m/s. A conical shaped thick plastic foil was used as a droplet collector and fixed on sample plant in three levels such as lower level, middle level and upper level of the plants. The distance between the sample plants to the UAV is 1 m and the arms of UAV to flat fan nozzle are 0.2 m. The tests were conducted at various speeds of rotors with 0% throttle, 50% of throttle and 100% throttle given by the radio transmitter. The height from the plant surface to the nozzle of UAV is approximately 0.5 m. The impact of the propeller’s rotational speeds differs from the distribution of the liquid on droplet collectors. The observations state the impact of the rotors rotational speeds are less at middle-level sample points. It shows approximately the same values in the three tests conducted at 0, 50, and 100% throttle rates are 34, 33, and 36%. The tests were conducted in an indoor environment to avoid wind speeds.

Farmers’ use of agricultural technology is necessary for reducing poverty. However, women make up most poor smallholder farmers in India and are generally unable to access relevant opportunities. Tandem to supporting women farmers in technology adoption is increasing their empowerment. While women’s empowerment has been on policy agendas in India for several years, progress has been slow and results are mixed. Using primary data from West Bengal, this study finds that female farmers with access to agricultural technologies will likely have social advantages over those without, but institutional and social support is necessary to facilitate real empowerment and overall development.

Food quality and safety are the two important factors that have gained ever-increasing attention in general consumers. Conventionally grown foods have immense adverse health effects due to the presence of higher pesticide residue, more nitrate, heavy metals, hormones, antibiotic residue, and also genetically modified organisms. Moreover, conventionally grown foods are less nutritious and contain lesser amounts of protective antioxidants. In the quest for safer food, the demand for organically grown foods has increased during the last decades due to their probable health benefits and food safety concerns. Organic food production is defined as cultivation without the application of chemical fertilizers and synthetic pesticides or genetically modified organisms, growth hormones, and antibiotics. The popularity of organically grown foods is increasing day by day owing to their nutritional and health benefits. Organic farming also protects the environment and has a greater socio-economic impact on a nation. India is a country that is bestowed with indigenous skills and potentiality for growth in organic agriculture. Although India was far behind in the adoption of organic farming due to several reasons, presently it has achieved rapid growth in organic agriculture and now becomes one of the largest organic producers in the world. Therefore, organic farming has a great impact on the health of a nation like India by ensuring sustainable development.