Abstract
Availability of low-cost imaging devices for embedded applications has enabled wireless multimedia sensor networks that can process and transmit image and video data in addition to scalar data. Such networks can be effectively employed to autonomously monitor: (i) the surface conditions and structural health of bridges and transport infrastructures at various geographical locations; (ii) the operational and environmental conditions of water wells and other life-critical resources in isolated areas. This paper describes an autonomous monitoring system. The paper focus is on critical transport infrastructure and natural resources in remote locations. The system identifies and reports the onset of anomalous conditions enabling infrastructure managers, government and community organizations to reduce service disruption, reduce risks and potentially save lives. This is beneficial to infrastructure owners, users and the local community. Initial system trials on infrastructure monitoring are presented, with further discussion of natural resources monitoring and disaster response in developing countries around the world. These provide a case- study for wider stakeholder involvement from government and public sector organizations, and NGOs.
Original language | English |
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Number of pages | 6 |
DOIs | |
Publication status | Published - 7 Sept 2015 |
Event | IEEEE- The International Conference on Computing, Control, Networking, Electronics and Embedded Systems Engineering (ICCNEEE 2015) - Sudan, Khartoum, Sudan Duration: 7 Sept 2015 → 9 Sept 2015 |
Conference
Conference | IEEEE- The International Conference on Computing, Control, Networking, Electronics and Embedded Systems Engineering (ICCNEEE 2015) |
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Country/Territory | Sudan |
City | Khartoum |
Period | 7/09/15 → 9/09/15 |
Bibliographical note
This paper won the best paper award in the Networking and Communications Track at the IEEE ICCNEEE2015 conference.The research described here is supported by the award made
by the RCUK Digital Economy program to the dot.rural Digital Economy Hub, reference: EP/G066051/1. The authors would like to acknowledge Shadin Alfadil for providing Khartoum water level data, Osama Fadlalla for the Nafeer community group report and information about Nafeer’s operations and Rashid Yahya Mudall for the insightful discussion and data on water levels of wells in the West of Sudan.
previously availabe at https://erg.abdn.ac.uk/research.php
Keywords
- Remote monitoring
- Energy Harvesting
- Embedded Systems
- Critical Infrastructure