Issa, A;
Odedeyi, T;
Darwazeh, I;
(2024)
IoT-Driven Precision Agriculture using Communication Technologies for Crop Quality and Real-time Environmental Monitoring.
In:
2024 IEEE 30th International Conference on Telecommunications, ICT 2024.
IEEE: Amman, Jordan.
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Abstract
This paper presents the development of an advanced system that merges real-time environmental monitoring and agronomical data analytics with yield and quality measurement to enable visualisation, analysis, modelling and long-term prediction of crop yield and quality based on environmental factors and farm practices. The system integrates Internet of Things (IoT) technologies and cloud-based analytics, incorporating Radio Frequency (RF) return loss measurements for non-destructive starch content assessment in cassava roots. The integrated data is transmitted through a custom-built pipeline to a web-based dashboard, offering real-time insights into the dynamic relationship between cassava yield and quality and environmental conditions. This system represents a significant advancement in the application of IoT for agriculture, providing a scalable framework for data-driven decision-making to enhance crop cultivation, with a potential impact on food security in cassava-dependent regions.
| Type: | Proceedings paper |
|---|---|
| Title: | IoT-Driven Precision Agriculture using Communication Technologies for Crop Quality and Real-time Environmental Monitoring |
| Event: | 2024 IEEE 30th International Conference on Telecommunications (ICT) |
| Dates: | 24 Jun 2024 - 27 Jun 2024 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/ICT62760.2024.10606133 |
| Publisher version: | https://doi.org/10.1109/ICT62760.2024.10606133 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Precision Agriculture, Cassava Cultivation, Starch Content Analysis, Environmental Monitoring, IoT, Cloud Analytics, ThingsBoard |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10197101 |
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