Edge Computing and AI-IoT Framework in Sustainable Rural Development
Aryan Rai
Scholar (B.Tech) Department of Computer Science & Engineering, Shri Ramswaroop Memorial University, Deva Road, Lucknow
RAbdul Rahman
Scholar (B.Tech) Department of Computer Science & Engineering, Shri Ramswaroop Memorial University, Deva Road, Lucknow
Ayush Kumar
Scholar (B.Tech) Department of Computer Science & Engineering, Shri Ramswaroop Memorial University, Deva Road, Lucknow
Farheen Siddiqui
Assistant Professor, Department of Computer Science & Engineering, Shri Ramswaroop Memorial University, Deva Road, Lucknow
Dr. Yusuf Perwej
Professor, Department of Computer Science & Engineering, Shri Ramswaroop Memorial University, Deva Road, Lucknow
📌 DOI: https://doi.org/10.63920/tjths.52009
🔑 Keywords: Edge AI-IoT, Offline Smart Village, LoRaWAN Mesh, Digital Twin, Hindi/Bhojpuri TTS, Sustainable Rural Development, Kanpur Dehat, Viksit Bharat @2047
📅 Publication Date: 05 April 2026
📜 License:
This work is licensed under a Creative Commons Attribution 4.0 International License
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Abstract:
Rural Uttar Pradesh, home to over 60% of the state’s 240 million residents, faces severe and interconnected challenges: 30–40% annual crop losses from erratic monsoons and undetected pests, 40% water wastage in traditional irrigation, doctor-to-patient ratios exceeding 1:10,000, power outages affecting 50% of villages for weeks, uncontrolled waste accumulation leading to groundwater contamination[8], and migration rates as high as 54% in aspirational districts. Government schemes such as Digital India, PM-KISAN, Jal Jeevan Mission, and NITI Aayog’s AI Roadmap provide essential support but remain reactive, cloud-dependent, costly (₹1–2 lakh per village), sector-siloed, English-only, and lacking predictive simulation tools. This paper presents VillageEdge AIoT – an original, unpublished, fully offline-first framework engineered specifically for Uttar Pradesh’s geo-climatic conditions, low-connectivity terrain, and linguistic diversity. The complete stack comprises ESP32-LoRa sensors for multi-parameter data collection, Raspberry Pi 5 edge gateways for local processing, TensorFlow Lite Micro machine-learning models for on-device inference, MQTT-LoRaWAN mesh networking (10–15 km range without cellular coverage), offline Hindi/Bhojpuri text-to-speech LLM (fine-tuned Piper + Whisper), and a Unity-based digital twin simulator for “what-if” policy testing. At a total hardware cost of only ₹45,000 per village cluster, the system operates 100% offline, consumes <1 W per node, runs on solar power, and seamlessly integrates six critical sectors—agriculture, healthcare, energy, waste management, education, and governance—under a single local dashboard
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📖 How to Cite
Aryan R., Abdul R., Ayush K., Farheen Siddiqui, Dr. Yusuf Perwej (2026). Edge Computing and AI-IoT Framework in Sustainable Rural Development. TEJAS J. Technol. Humanit. Sci.,, Vol. 05, Issue 02. https://doi.org/10.63920/tjths.52009
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