Nowadays, artificial intelligence and machine learning are being used in various agricultural applications.
But what are artificial intelligence and machine learning and how can they be used for agriculture?
Artificial intelligence (AI) is a concept that uses computers and machines to replicate the human mind’s problem-solving and decision-making abilities. Machine learning (ML), on the other hand, is a subset of AI that focuses on using data and algorithms to mimic the way humans learn while continuously improving accuracy.
ML is being utilised in agriculture to increase crop output and quality. Seed retailers combine the data with agricultural technology to develop better crops. It is used by pest control firms to identify different bacteria, bugs, and vermin. AI is used to determine which conditions will offer the highest yield.
Additionally, many businesses are increasingly employing deep learning algorithms and technology. Drones and other software are being used to gather data on the crops and the soil. They also work on the software to manage the soil's fertility. Farmers can find effective strategies to save their produce and protect it from weeds by using innovative agricultural technologies. For the food technology industry, AI and ML are beneficial because crops are being managed and monitored by robots. Sensors assist in the collection of crop-related data.
However, it is not that easy…
To maximise efficiency, the future of farming lies in collecting and analysing data. To develop effective AI solutions and understand how smallholder farmers can use AI and ML, agri-tech companies need high-quality data. ML requires a lot of it; however, a large gap in data collection, preparation and benchmarking capabilities still exists today. This makes modelling a challenge.
Farmer Charlie aims to overcome these challenges bringing Wi-Fi internet connectivity to the field, weather and field sensors, and high-quality data evaluation to make farming more efficient for smallholder farmers.
-Farid Ibtida Tashbeeh
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