| dc.contributor.author | Mbele, Mpho | |
| dc.contributor.author | Masinde, Muthoni | |
| dc.contributor.author | Kgololo-Ngowi, Itumeleng | |
| dc.date.accessioned | 2018-10-18T08:28:24Z | |
| dc.date.available | 2018-10-18T08:28:24Z | |
| dc.date.issued | 2016 | |
| dc.identifier.uri | http://hdl.handle.net/11462/1687 | |
| dc.description | Conference Proceedings | en_US |
| dc.description.abstract | South Africa is home to some of the deepest mines in the world. Waste from gold mines constitutes the largest single source of waste and pollution in South Africa [2] Though mining industries develop environmental management systems/plans to identify and mitigate the impacts their operations has on the society, their outcome still poses a threat in terms of environmental pollution to communities around them. There are many ICT-based pollution monitoring solutions, but they do not address the needs of the affected mining communities. Some of the reasons for this include lack of relevant tools to access the systems (smartphones, computers) as well as lack of understanding and appreciation of the disseminated information. The mining communities around Lejweleputswa (South Africa) have learnt to depend on their own local knowledge to prevent or mitigate the impacts that mining operations has on them. | en_US |
| dc.format.extent | 148 836 bytes, 1 file | |
| dc.format.mimetype | Aplication/PDF | |
| dc.language.iso | en_US | en_US |
| dc.publisher | ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering | en_US |
| dc.subject | Fuzzy cognitive maps | en_US |
| dc.subject | Wireless sensor networks | en_US |
| dc.subject | Adaptive | en_US |
| dc.subject | Local communities | en_US |
| dc.title | Adaptive Environmental Management System for Lejweleputswa District: A Participatory Approach Through Fuzzy Cognitive Maps | en_US |
| dc.type | Presentation | en_US |