किसानों की पीड़ा और उसका समाधान -एस. के . सिंह - Gramin Samridhi Foundation working touse Artificial Intelligence(AI)in Agriculture
According to Nasscom-BCG report, India’s Artificial Intelligence market is poised to $27 Billion by 2027. AI was rated as the top category of IT spending in 2023. India’s AI market is projected to grow at 25% Compound Annual Growth Rate (CAGR) till 2027. If Artificial intelligence drives a new Industrial revolution, alongside new concentration of wealth and power, the only way for India to be at high table will be to be an Artificial Intelligence maker and just an Artificial Intelligence taker. As much as 96% of wealth gained on the Bloomberg Billionaires index in 2023-24 is Artificial Intelligence related stocks. Globally, investment in AI have seen 24%CAGR since 2019 and till 2023 a huge sum of $83 Billion invested.
India missed the Product development bus in 90s when IT boom touched the country and very few companies dared to have startups for product and IP development in India. But now the scenario has changed and India is the 3rd preferred destination for Product and IP after USA and UK. Thanks to the young and risk-taking technical youths of the country the startup landscape is likely to have more participation. AI in Agriculture has a huge potential and Gramin Samridhi Foundation has taken an initiative to develop and integrate the requisite indigenous IP/ technologies of Artificial Intelligence for Agriculture and farming and roll out its first product with limited features of AI by 2025.
What is artificial intelligence (AI) and how does it work?: Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision. In general, AI systems work by ingesting large amounts of labelled training data, analysing the data for correlations and patterns, and using these patterns to make predictions about future states.
Population Pressure on food requirements : The growth of the global population, which is projected to reach 10 Billion by 2050, is placing significant pressure on the agricultural sector to increase crop production and maximize yields. To address looming food shortages, two potential approaches have emerged: 1) expanding land use and adopting large-scale farming or 2) embracing innovative practices and leveraging technological advancements to enhance productivity on existing farmland. Pushed by many obstacles to achieving desired farming productivity — limited land holdings, labour shortages, climate change, environmental issues, and diminishing soil fertility, to name a few, — the modern agricultural landscape is evolving, branching out in various innovative directions. Farming has certainly come a long way since hand ploughs or ox-drawn machinery to tractors & automated agricultural tools. Each season brings new technologies designed to improve efficiency and capitalize on the harvest. However, both individual farmers and global agribusinesses often miss out on the opportunities that Artificial Intelligence in agriculture can offer to their farming methods.
Agriculture & Civilization : There is a famous leader of middle east who once said, “Give me Agriculture and I will give you civilization”. So, Agriculture is also important to keep our civilization alive! After all, Agriculture has been the backbone of human civilization for millennia, providing sustenance as well as contributing to economic development. In corona time when almost all the industries were hit tanks to Agriculture and our social wisdom which came to the rescue of mankind and kept us alive.
Bihar & Agriculture : Bihar lies in the river plains of the basin of the river Ganga. As a result, its land contains fertile alluvial soil and groundwater resources. This makes the agriculture of Bihar rich and diverse. Rice, wheat, and maize are the major cereal crops. Arhar, urad, moong, gram, pea, lentils, and khesari are some of the pulses cultivated in Bihar. Bihar is the fourth largest producer of vegetables, which is dominated by potato, onion, eggplant, and cauliflower. In fruit cultivation, it is the largest producer of lychee and the third largest producer of pineapple, as well as a major producer of mango, banana, and guava. Sugar cane and jute are two other major cash crops of Bihar. As of 2021, Agriculture accounts for 24%, industry 15% and service 61% of the economy of the state.
Benefits of Artificial Intelligence in Agriculture & farming : Innovations and disruptive engineering interventions in Agriculture are becoming increasingly essential as global challenges such as climate change, population growth together with resource scarcity threaten the sustainability of our food system. Introducing Artificial Intelligence solves many challenges and helps to diminish many disadvantages of traditional farming.
1. Data-based decisions : The modern world is all about data. Organizations in the agricultural sector use data to obtain meticulous insights into every detail of the farming process, from understanding each acre of a field to monitoring the entire produce supply chain to gaining deep inputs on yields generation process. AI-powered predictive analytics is already paving the way into agribusinesses. Farmers can gather, then process more data in less time with AI. Additionally, AI can analyse market demand, forecast prices as well as determine optimal times for sowing and harvesting. Artificial intelligence in agriculture can help explore the soil health to collect insights, monitor weather conditions, and recommend the application of fertilizer and pesticides. Farm management software boosts production together with profitability, enabling farmers to make better decisions at every stage of the crop cultivation process.
2. Cost savings : Improving farm yields is a constant goal for farmers. Combined with AI, precision agriculture can help farmers grow more crops with fewer resources. AI in farming combines the best soil management practices, variable rate technology, and the most effective data management practices to maximize yields while minimizing spending. Application of AI in agriculture provides farmers with real-time crop insights, helping them to identify which areas need irrigation, fertilization, or pesticide treatment. Innovative farming practices such as vertical agriculture can also increase food production while minimizing resource usage.
3. Automation impact : Agricultural work is hard, so labour shortages are nothing new. Thankfully, automation provides a solution without the need to hire more people. While mechanization transformed agricultural activities that demanded super-human sweat and draft animal labour into jobs that took just a few hours, a new wave of digital automation is once more revolutionizing the sector. Automated farm machinery like IoT-powered agricultural drones, smart spraying, vertical farming software, and AI-based greenhouse robots for harvesting are just some examples. Compared with any human farm worker, AI-driven tools are far more efficient and accurate.
4. Optimizing automated irrigation systems : AI algorithms enable autonomous crop management. When combined with IoT (Internet of Things) sensors that monitor soil moisture levels and weather conditions, algorithms can decide in real-time how much water to provide to crops. An autonomous crop irrigation system is designed to conserve.
5. Detecting leaks or damage to irrigation systems : AI plays a crucial role in detecting leaks in irrigation systems. By analysing data, algorithms can identify patterns and anomalies that indicate potential leaks. Machine learning (ML) models can be trained to recognize specific signatures of leaks, such as changes in water flow or pressure. Real-time monitoring and analysis enable early detection, preventing water waste together with potential crop damage. AI also incorporates weather data alongside crop water requirements to identify areas with excessive water usage. By automating leak detection and providing alerts, AI technology enhances water efficiency helping farmers conserve resources.
6. Crop and soil monitoring : The wrong combination of nutrients in soil can seriously affect the health and growth of crops. Identifying these nutrients and determining their effects on crop yield with AI allows farmers to easily make the necessary adjustments. While human observation is limited in its accuracy, computer vision models can monitor soil conditions to gather accurate data. This plant science data is then used to determine crop health, predict yields while flagging flag any particular issues. In practice, AI has been able to accurately track the stages of wheat growth and the ripeness of tomatoes with a degree of speed and accuracy no human can match.
7. Detecting disease and pests : As well as detecting soil quality and crop growth, computer vision can detect the presence of pests or diseases. This works by using AI to scan images to find mold, rot, insects, or other threats to crop health. In conjunction with alert systems, this helps farmers to act quickly in order to exterminate pests or isolate crops to prevent the spread of disease. AI has been used to detect apple black rot with an accuracy of over 90%. It can also identify insects like flies, bees, moths, etc., with the same degree of accuracy. However, researchers first needed to collect images of these insects to have the necessary size of the training data set to train the algorithm with.
8. Monitoring livestock health : It may seem easier to detect health problems in livestock than in crops, in fact, it’s particularly challenging. Thankfully, AI can help with this. For example, a company called CattleEye has developed a solution that uses drones, cameras together with computer vision to monitor cattle health remotely. It detects atypical cattle behavior and identifies activities such as birthing. CattleEye uses AI and ML solutions to determine the impact of diet alongside environmental conditions on livestock and provide valuable insights. This knowledge can help farmers improve the well-being of cattle to increase milk production.
9. Intelligent pesticide application : By now, farmers are well aware that the application of pesticides is ripe for optimization. Unfortunately, both manual and automated application processes have notable limitations. Applying pesticides manually offers increased precision in targeting specific areas, though it might be slow and difficult work. Automated pesticide spraying is quicker and less labour-intensive, but often lacks accuracy leading to environment contamination. AI-powered drones provide the best advantages of each approach while avoiding their drawbacks. Drones use computer vision to determine the amount of pesticide to be sprayed on each area. While still in infancy, this technology is rapidly becoming more precise.
10. Yield mapping and predictive analytics : Yield mapping uses ML algorithms to analyze large datasets in real time. This helps farmers understand the patterns and characteristics of their crops, allowing for better planning. By combining techniques like 3D mapping, data from sensors and drones, farmers can predict soil yields for specific crops. Data is collected on multiple drone flights, enabling increasingly precise analysis with the use of algorithms. These methods permit the accurate prediction of future yields for specific crops, helping farmers know where and when to sow seeds as well as how to allocate resources for the best return on investment.
11. Automatic weeding and harvesting : Similar to how computer vision can detect pests and diseases, it can also be used to detect weeds and invasive plant species. When combined with machine learning, computer vision analyses the size, shape, and colour of leaves to distinguish weeds from crops. Such solutions can be used to program robots that carry out robotic process automation (RPA) tasks, such as automatic weeding. In fact, such a robot has already been used effectively. As these technologies become more accessible, both weeding and harvesting crops could be carried out entirely by smart bots.
12. Sorting harvested produce : AI is not only useful for identifying potential issues with crops while they’re growing. It also has a role to play after produce has been harvested. Most sorting processes are traditionally carried out manually however AI can sort produce more accurately. Computer vision can detect pests as well as disease in harvested crops. What’s more, it can grade produce based on its shape, size, and colour. This enables farmers to quickly separate produce into categories — for example, to sell to different customers at different prices. In comparison, traditional manual sorting methods can be painstakingly labour-intensive.
13. Surveillance : Security is an important part of farm management. Farms are common targets for burglars, as it’s hard for farmers to monitor their fields around the clock. Animals are another threat — whether it’s foxes breaking into the chicken coop or a farmer’s own livestock damaging crops or equipment. When combined with video surveillance systems, computer vision and ML can quickly identify security breaches. Some systems are even advanced enough to distinguish employees from unauthorized visitors.
Gramin Samridhi Foundation has started working on design and implementation of AI Algorithms and requisite state of the art hardware for electronic system design in association with other stakeholders for making the Agriculture and Allied Agriculture easy and productive by using AI. The first product under design is a software defined solar based mini tractor having the capabilities of AI for some of the usage mentioned above. The proof of concept with limited features of AI is likely to be ready by next year for field trials. Subsequently more and more AI features of AI will be implemented down the line to position this as an indigenous product as a game changer for India. The next AI enabled product from Gramin Samridhi Foundation which is under technical formulation is AI based smart home suitable for rural population. This effort of Gramin Samridhi Foundation will also break the myth that only Company can create Intellectual Property (IP) and Product. NGOs down the line in India have got to play roles right from defining the technical solution to taking them to the common people for the prosperity of the society and to make their life easy. (Courtesy to https://intellias.com/artificial-intelligence-in-agriculture/ for the content on use of AI in Agriculture and Times of India news on AI market Research)
