AI can be integrated with other emerging technologies in agriculture, such as blockchain and IoT, to enhance farming practices in several ways. Firstly, AI can be used to analyze data collected from IoT sensors, such as weather data, soil moisture levels, and crop health data, to predict crop yields and optimize irrigation and fertilization schedules. Secondly, blockchain technology can be used to create smart contracts that automatically execute when certain conditions are met, such as releasing payment to a farmer when a shipment of crops reaches a certain quality standard. AI can be used to analyze data from IoT sensors to determine when the conditions for executing a smart contract have been met. Thirdly, blockchain can be used to create a transparent and secure supply chain for agricultural products, with IoT devices used to track the location and condition of crops and livestock throughout the supply chain. AI can be used to analyze this data to identify inefficiencies and optimize the supply chain. Finally, AI can be used to identify areas of a farm that require more or less attention through the analysis of data from IoT sensors such as satellite imagery and weather data. Blockchain can be used to create a tamper-proof record of these activities, providing transparency and accountability.

AI can be integrated with other emerging technologies such as blockchain and IoT in agriculture to improve productivity, efficiency, and sustainability. Here are some ways in which AI can be integrated with these technologies:

Using AI to analyze data collected by IoT sensors: IoT sensors can be used to collect data on soil moisture, temperature, and other environmental factors. AI algorithms can analyze this data to provide insights on when to plant, irrigate, and harvest crops. By using AI to analyze IoT data, farmers can optimize their operations and reduce waste.

Using blockchain to trace the origin of food: Blockchain technology can be used to create a secure, decentralized database of information about the origin and quality of food. By integrating AI with blockchain, it becomes possible to track the entire supply chain of food, from the farm to the table. AI can help analyze this data to identify trends and patterns that can improve the efficiency and sustainability of the food system.

Using AI to predict crop yields: AI algorithms can be trained to predict crop yields based on historical data, weather patterns, and other environmental factors. By combining these predictions with data from IoT sensors, farmers can optimize their operations and make more informed decisions about when to plant, irrigate, and harvest crops.

Using blockchain to facilitate payments: Blockchain technology can be used to facilitate payments between farmers, distributors, and retailers. By using smart contracts and other blockchain-based payment systems, farmers can receive payment more quickly and efficiently, reducing the financial risk of farming.

Dear Sudip Ghimire,

applying the idea of Digital Twins (DTs) to agriculture opens up the possibility of integrating AI with other emerging technologies such as Blockchain and IoT. The attached literature should confirm this and give suggestions.

For a well-illustrated idea of using AI in IoT see my info source:

https://www.researchgate.net/publication/366167747_Digital_Twins_in_IoT

Best regards and much success

Anatol Badach

Christos Pylianidis, Sjoukje Osinga, Ioannis N. Athanasiadis: Introducing digital twins to agriculture; Computers and Electronics in Agriculture, Vol. 184, Mar 2021; DOI: 10.1016/j.compag.2020.105942

Rafael Gomes Alves, Gilberto Souza, Rodrigo Filev Maia, Juan Manuel Davila.: A digital twin for smart farming; IEEE Global Humanitarian Technology Conference (GHTC), Oct 2019, DOI: 10.1109/GHTC46095.2019.9033075

Cor Verdouw, Bedir Tekinerdogan, Adrie J. M. Beulens, Sjaak Wolfert: Digital twins in smart farming; Agricultural Systems, Vol. 189(15), Apr 2021; DOI: 10.1016/j.agsy.2020.103046

Suresh Neethirajan, Bas Kemp: Digital Twins in Livestock Farming; Animals, Vol. 11 Issue 4, Apr 2021, DOI: 10.3390/ani11041008

AI/ML together with IoT is proving a powerful force for building connections between the monitoring, predictive and operationalisation decision making. These connections enable on the ground decisions in relation to farm operation to be optimised and enhanced in areas such as irrigation, fertilising etc. Integrating these capabilities with farm machinery can also program and automate some of the key activities on a farm.