Advancements in IoT-Based Data Logging for Crop Evapotranspiration Monitoring: Trends and Challenges: A Review

Onyemechara Idong-esit Comfort, Chukwuemeka Etus, Emeka Mathew Nwanga, Egbe Toochi Paul, Anwar Cassia Chinweaku and Jane Chidinma Daniel-Nwaizuzu
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Onyemechara Idong-esit Comfort: Department of Computer Science, Federal Polytechnic Nekede, Owerri Nigeria
Chukwuemeka Etus: Department of Information Technology, Federal University of Technology Owerri, Nigeria
Emeka Mathew Nwanga: Department of Information Technology, Federal University of Technology Owerri, Nigeria
Egbe Toochi Paul: Department of Computer Science, Federal Polytechnic Nekede, Owerri Nigeria
Anwar Cassia Chinweaku: Department of Computer Science, Federal Polytechnic Nekede, Owerri Nigeria
Jane Chidinma Daniel-Nwaizuzu: Department of Agricultural Technology, Federal Polytechnic Nekede, Owerri Nigeria

International Journal of Latest Technology in Engineering, Management & Applied Science, 2025, vol. 14, issue 3, 354-360

Abstract: The Internet of Things (IoT) integration with agriculture has brought revolutionary changes to the field of data collection and analysis through agricultural evapotranspiration (ET) monitoring. IoT data logging systems integrate advanced sensors with wireless networks and cloud computing which enable real-time monitoring of soil moisture as well as soil temperature and humidity and atmospheric environmental conditions. Through innovative technological developments farmers can establish precise irrigation systems that enhance water resources and yield production and respond effectively to environmental changes. The Internet of Things delivers essential functions for precise agriculture by enabling automatic data acquisition and distant system monitoring basics for better decision-making. Current advancements in ET technologies involve the manufacturing of advanced sensors which combine high accuracy capabilities with low power consumption while using advanced communication systems with extensive range capabilities and artificial intelligence systems for forecasting ET estimations. The slow adoption rate of IoT in agriculture is affected by several barriers including the high costs of implementation as well as rural area network connectivity problems and security risks related to data protection. Better future research will concentrate on sensor price reduction along with better network infrastructure and AI algorithms for optimizing ET prediction accuracy. Increasing reliability along with efficiency in IoT agricultural systems requires tackling these specific issues. The potential of monitoring ET rates through IoT technology shows great promise to transform how farmers manage their water supply. Global food security becomes more sustainable through IoT enabled data-driven irrigation which reduces water wastage and enables superior crop production.

Date: 2025
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