siliconindia | | February 20199precious data) to identify patterns and make predictions. In countries like India that lack required human capital in fields like agricultural science and lower coverage of adequate information, AI presents an opportunity to bridge the gap and deliver sustainable results.Bringing the Confidence in UncertaintyNewest AI-led applications and tech-nologies are disrupting the agricul-tural space every day and creating a platform for better preventive mea-sures, yield productivity, and re-source utilization. We can categorize the current applications based on the solutions into four major categories. In crop and soil monitoring segment, image analytics, soil variability mea-surement, deep learning algorithms are being leveraged by companies for processing captured data and offer-ing accurate solutions in a relatively short period. The automated irriga-tion segment has shown disruptive advancements by enabling AI and data-driven automated irrigation, fertilizer application with irrigation (Fertigation) and crop protection. Innovative products capable of moni-toring, analysing, and controlling the irrigation backed by AI have already been introduced in the market with the consistent addition of advanced features. With irrigation as the most important input to any crop and 70 percent of the world's freshwater used for agriculture, the ability to better manage how it's used will also have a huge impact on the world's water supply and not just limited to agriculture.Predictive analytics covers an entire solution range that made guesses about the future of farming, not a magic dependent, but a data science-based one. Infield sensors, remote sensing inputs, and several data points help to take a well-informed decision much easier. Machine learning models and algorithms based on past & present factors in the field, along with environmental factors help to make an accurate prediction of each step of farming. Many technological organizations are already assisting farming at right sowing time, right irrigation schedule, expected pest attack and various other factors through predictive analytics. This is now being explored in improving supply chain efficiencies in agriculture as well. Agricultural Robotics segment backed by sturdy hardware and software alignment is currently used, and proponents of the robotics market are developing and programming offerings that are equipped with the intelligence to handle essential agricultural tasks and operate in unstructured and dynamic agricultural environments.Precision Farming & AI a Necessity A Global Harvest Initiative report pointed-out that at the current rate of agricultural productivity growth in India, domestic production will only meet 59 percent of the country's food demand by 2030. That means around 600 million people will be dependent on imports or will face minimal food availability. The variability in farming due to external factors is on an exponential increase with the change in weather patterns, rainfall variability, and new pest attacks. It needs an exponentially developing technology like AI to counter the effects and led to a sustainable environment of growth and productivity improvement in agriculture. Food and water, two of the most important constituents of earth sustainable life, are under severe stress ­ World needs to double our food production by 2050 to match the population growth, and 20 percent of the world population faces water shortages today as per the UN report (India is under severe water stress category). With depleting resources
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