Sustainable Peatland Management with IoT and Data Analytics
| Autor: | Jiun Terng Liew, Borhanuddin Mohd Ali, Nor Kamariah Noordin, Yacine Ouzrout, Aduwati Sali, Syamsiah Mashohor, Nur Luqman Saleh, Aicha Sekhari, Fazirulhisyam Hashim |
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| Přispěvatelé: | Faculty of Engineering, Universiti Putra Malaysia, Serdang, Selangor, Universiti Putra Malaysia, Université Lumière - Lyon 2 (UL2), Luis M. Camarinha-Matos, Xavier Boucher, Hamideh Afsarmanesh |
| Rok vydání: | 2021 |
| Předmět: |
IoT
0209 industrial biotechnology Peat 02 engineering and technology [SPI]Engineering Sciences [physics] Upload 020901 industrial engineering & automation 020401 chemical engineering Machine learning 0204 chemical engineering business.industry Environmental resource management 15. Life on land Livelihood 6. Clean water Critical level 13. Climate action Agriculture Greenhouse gas Sustainability Environmental science peatland CPS sustainable Internet of Things business |
| Zdroj: | IFIP Advances in Information and Communication Technology ISBN: 9783030859688 PRO-VE IFIP Advances in Information and Communication Technology 22nd IFIP WG 5.5 Working Conference on VIRTUAL ENTERPRISES, PRO-VE 2021 22nd IFIP WG 5.5 Working Conference on VIRTUAL ENTERPRISES, PRO-VE 2021, Nov 2021, Saint-Etienne, France. 10p, ⟨10.1007/978-3-030-85969-5_51⟩ |
| Popis: | International audience; Peatland is important to rural communities’ livelihood due to its potential for aquaculture and agriculture. Nonetheless, human activities such as slash-and-burn can greatly increase forest fire risk, which can release a great amount of greenhouse gases and carbon dioxide into the atmosphere. To sustainably manage and restore peatlands, the Internet of Things (IoT) system can incorporate with Cyber-Physical System (CPS) for peatland management. In this study, an IoT system is deployed in the peatland to monitor the ground water level (GWL) and upload it to the server for the machine learning (ML) process. The trend of GWL will be modelled, and the CPS using the developed ML model will control the peatland rewatering process. As a result, the peatland condition can be monitored in real-time, and the risk of forest fire can be mitigated through rewatering automation before the GWL drops to a critical level. |
| Databáze: | OpenAIRE |
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