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A Monitoring and Rescuing System Using Next Generation Mobile, Internet of Things and Artificial Intelligence for Freshwater Lakes in Africa
Bahir Dar University, Bahir Dar Institute of Technology,Bahir Dar,Ethiopia.
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0009-0006-6443-4483
CSIR,Defence & Security,Pretoria,South Africa.
2023 (English)In: 2023 IEEE AFRICON, Institute of Electrical and Electronics Engineers (IEEE), 2023Conference paper, Published paper (Refereed)
Abstract [en]

In this paper an experimental system assisted by emerging digital technologies is developed, for monitoring and controlling invasive water hyacinth weed and rescue operation of freshwater lakes in Africa. The system is designed to integrate fifth generation ultra-reliable low latency communication (5G URLLC), unmanned aerial vehicles (UAV), underwater robots, smart environmental sensing with internet of things (IoT) and machine learning techniques for real time monitoring, managing, controlling and predicting the expansion of invasive water hyacinth weed. The experimental system for sensor data collection implemented on lake Tana in Ethiopia will be expanded to other fresh water lakes of Africa affected by water hyacinth weed. System modeling and data analytics based on sensor data will be performed to generate decision inference for controlling the growth of water hyacinth in the water bodies of the lake. Environmental data collection from other local sources will be integrated with sensor data for further system modeling and critical action analysis and implementation using machine learning algorithms to remove the main causes for the rapid expansion of water hyacinth throughout the lake.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023.
Series
Proceedings, African Electrical Technology Conference, ISSN 2153-0025, E-ISSN 2153-0033
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:mau:diva-63757DOI: 10.1109/africon55910.2023.10293273Scopus ID: 2-s2.0-85177682452ISBN: 979-8-3503-3622-1 (print)ISBN: 979-8-3503-3621-4 (electronic)OAI: oai:DiVA.org:mau-63757DiVA, id: diva2:1813251
Conference
IEEE AFRICON 2023, Nairobi, Kenya, September 20-22, 2023
Available from: 2023-11-20 Created: 2023-11-20 Last updated: 2023-12-07Bibliographically approved

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Mekuria, Fisseha

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