A Review of Using Artificial Intelligence and Machine Learning in Food and Agriculture Industry

Food needs are rising as the world's population grows. Similarly, the food processing industry is growing at an accelerated pace. Reduced food waste, better supply chain management, and increased delivery and storage of food are urgently required. These goals can be achieved to a large part with the use of artificial intelligence and machine learning. When a computer software can learn to anticipate future events without being programmed, it is known as machine learning. Supervised learning and unsupervised learning are two of the most common subcategories of machine learning. In this post, we'll look at how AI and machine learning are being used in the food and agricultural sector. Supply chain optimization, crop selection, logistics, food delivery, maintenance prediction in food processing machinery, detection of crop disease, smart irrigation, crop yield prediction, tracking of perishable food, soil data analysis, and weather data analysis are all major applications.