Harvesting Data. The Role of AI and Big Data in Modern Agriculture Technologies
The majority of the procedures and steps involved in agriculture are manual. AI may assist the most challenging and ordinary jobs by enhancing current technology. Automation can help farmers address labor shortages by using driverless tractors, intelligent irrigation & fertilizing systems, smart spraying, vertical farming software, and AI-based harvesting robots, to name just a few. AI-driven farm machinery is more efficient, productive, and quick than any human worker.
Big Data and AI work together to improve agriculture
The success of AI in agriculture greatly depends on data, which serves as the backbone of its algorithms. These algorithms rely on vast amounts of data collected from various sources. Technological tools can assist farmers in collecting and utilizing data to manage their crops more precisely, resulting in reduced greenhouse gas emissions. By obtaining better soil and plant health data, farmers can identify areas where irrigation, pesticide, and fertilizer use need to be increased or decreased. These practices save farmers money, increase productivity, and generate more food with less waste.
AI algorithms assist in enhancing farming decisions by analyzing data for planting, harvesting, and pest control. Drones equipped with AI sensors detect diseases and pests early, while historical data helps predict potential challenges. Optimal water usage is ensured by analyzing moisture data, and AI streamlines the supply chain for improved product delivery and reduced waste. Soil health is monitored for timely treatments, and autonomous tractors improve efficiency. AI also assesses climate change impacts and develops adaptable crop varieties for sustainable farming practices.
According to a recent study, AI and data analytics have the potential to save up to $250 billion annually. Big data in agriculture offers numerous benefits, such as increased farming productivity through forecasting crop production and improving crop yields. Additionally, data analysis helps reduce the consumption of resources like water and electricity, making farming operations more efficient. By embracing technology, agriculture can become more attractive to specialists and prevent them from seeking other occupations. Another significant advantage of AgriTech is the reduction of food waste. Currently, between 20% to 30% of food is wasted at different supply chain stages. By addressing this issue, AgriTech can save up to $155–405 billion annually by 2030.
Market and Trends
The worldwide market for artificial intelligence in agriculture was valued at USD 1.37 billion in 2022. It is projected to reach approximately USD 11.13 billion by 2032, growing at a significant CAGR of 23.3% between 2023 and 2032.
According to AgFunder Global AgriFoodTech Investment Report, Global investment in FoodTech and AgroTech startups totaled $29.6bn in 2022.
The AgriTech industry is experiencing significant growth in the field of artificial intelligence. This can be attributed to several factors, such as the increasing population and demand for food, technological advancements, greater reliance on data-driven decisions, drone, and robotics technology improvements, increased government support, the broader use of AI for crop surveillance, and more investments in AgTech startups.
The 2022 data clearly showed a trend towards early-stage innovations. Venture capitalists anticipate this trend to persist into 2023, particularly in the realm of Agricultural Biotechnology. This encompasses areas like synthetic biology, alternative biological crop inputs, and genetic modification.
Conclusion
AI and Big Data are key to the future of agriculture. They streamline processes and promote sustainability. Ethical data collection and application are crucial for success. The next decade will set the stage for a responsible and advanced agricultural landscape capable of feeding the world's population while preserving the environment.
