Bakirov K., Shoman A., Tussupov J., Shayea I., Dauletiya D., Mekesh S.
Engineering Smart Agricultural Systems: Leveraging IoT and AI for Sustainable Urban Farming // Proceedings of the 2025 IEEE European Technology and Engineering Management Summit (E-TEMS). — 2025. — Conference held 26–28 May 2025. — DOI: 10.1109/E-TEMS64751.2025.11239298.

Abstract: This paper presents a comprehensive framework for smart agricultural systems using Internet of Things (IoT) and Artificial Intelligence (AI) technologies for sustainable urban farming. To address challenges such as food scarcity, limited arable land, and environmental constraints in urban areas, a vertical farming system is designed and implemented using IoT sensor networks including DHT11 temperature and humidity sensors and lux light intensity sensors, along with manual plant height measurements for real-time monitoring. Data were collected at one-minute intervals over two weeks using both cloud and local systems to ensure robust and scalable acquisition. Short-term temperature forecasting for proactive climate control was performed using classical time series models (ARIMA) and deep learning (LSTM). Results show that while ARIMA provides strong baseline performance, LSTM achieves better accuracy, demonstrating the advantages of AI-based predictive control in indoor farming systems. The proposed framework improves environmental stability and energy efficiency, contributing to the development of sustainable smart urban agriculture systems.

Link / DOI: https://doi.org/10.1109/E-TEMS64751.2025.11239298