August 25, 2025Scientific ReportsOpen Access

On-device AI for climate-resilient farming with intelligent crop yield prediction using lightweight models on smart agricultural devices

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Observational analysis boosts crop yield prediction in smart agriculture, indicating improved water management.

The model achieved 90.1% accuracy in predicting crop yield, surpassing existing AI-enabled methods that ranged from 87.2% to 89%.
Experimental validation on real-time agricultural data established effective water management, emphasizing efficiency in irrigation practices.
The random forest algorithm deployed supports real-time decision-making, eliminating the need for cloud computing, which enhances responsiveness and reduces latency.
These efforts may enable climate-resilient farming practices, which are critical as environmental challenges continue to rise in prominence.

Dhanaraj et al. (2025) studied this question.

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