AI-Driven Smart Agriculture: An Intelligent Farming System Using AI, IoT, ESP32, Edge AI, and Smart Solar Irrigation

Agriculture is the mainstay of the Indian economy, However, water insecurity, climate variability and degradation of soils are the challenges faced by farmers. Increasing energy prices and crop diseases. Existing studies show that Artificial Intelligence (AI), the Internet of Things (IoT), Edge AI, It is believed that computer vision and smart irrigation could be applied to enhance agricultural production. They are typically used for decision-making and resource use, although the use of them is not always restricted. independently, rely on internet connection or cloud computing, Still be expensive for small and mediumsized farmers. This paper surveys eight recent studies from 2022 to 2026, derives seven research gaps from them, and proposes a conceptual, affordable platform that combines an ESP32 microcontroller, soil and environmental sensors, Edge AI-based crop and fertilizer recommendation, computer-vision detection of crop diseases, pests and weeds, solar-powered smart irrigation, and a mobile application with a multilingual voice assistant. An evaluation plan is also given. The contribution is a literature-grounded design and research agenda; the platform has not yet been implemented or empirically validated.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-29
DOI
https://doi.org/10.5281/zenodo.23770730
Primary Topic
Smart Agriculture and AI
Type
article
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article

AI-Driven Smart Agriculture: An Intelligent Farming System Using AI, IoT, ESP32, Edge AI, and Smart Solar Irrigation

Jayshree Suryawanshi, Namrata Jori
1 links
Zenodo (CERN European Organization for Nuclear Research)
Smart Agriculture and AI
article

AI-Driven Smart Agriculture: An Intelligent Farming System Using AI, IoT, ESP32, Edge AI, and Smart Solar Irrigation

Jayshree Suryawanshi, Namrata Jori
article en

Abstract

Agriculture is the mainstay of the Indian economy, However, water insecurity, climate variability and degradation of soils are the challenges faced by farmers. Increasing energy prices and crop diseases. Existing studies show that Artificial Intelligence (AI), the Internet of Things (IoT), Edge AI, It is believed that computer vision and smart irrigation could be applied to enhance agricultural production. They are typically used for decision-making and resource use, although the use of them is not always restricted. independently, rely on internet connection or cloud computing, Still be expensive for small and mediumsized farmers. This paper surveys eight recent studies from 2022 to 2026, derives seven research gaps from them, and proposes a conceptual, affordable platform that combines an ESP32 microcontroller, soil and environmental sensors, Edge AI-based crop and fertilizer recommendation, computer-vision detection of crop diseases, pests and weeds, solar-powered smart irrigation, and a mobile application with a multilingual voice assistant. An evaluation plan is also given. The contribution is a literature-grounded design and research agenda; the platform has not yet been implemented or empirically validated.

Zenodo (CERN European Organization for Nuclear Research)
Zero hunger, Industry, innovation and infrastructure
Openalex Percentile: Top 15%
Smart Agriculture and AI
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