Internet of Things (IoT)‐based aquaculture: An overview of IoT application on water quality monitoring

• Published in: Reviews in aquaculture Vol. 14; no. 2; pp. 979 - 992
• Main Authors: Prapti, Dipika Roy, Mohamed Shariff, Abdul Rashid, Che Man, Hasfalina, Ramli, Norulhuda Mohamed, Perumal, Thinagaran, Shariff, Mohamed
• Format: Journal Article
• Language: English
• Published: Burwood Wiley Subscription Services, Inc 01-03-2022
• Subjects: Aquaculture; Aquaculture 4.0; aquaculture water quality; aqua‐tech; Dissolved oxygen; Experimental research; Fish industry; Fish ponds; Fishing; Fishponds; Industrial Revolution 4.0; Internet of Things; Laboratory experimentation; Marine aquaculture; Monitoring; Parameters; Scientific papers; smart aquaculture; Water monitoring; Water quality; Water quality management; water quality monitoring
• ISSN: 1753-5123; 1753-5131
• DOI: 10.1111/raq.12637

Aquaculture based on the Internet of Things (IoT) is a growing field of interest in the fishing industry. The IoT technology is advancing the agriculture 4.0 era, and yet, Aquaculture 4.0 is a lagging field in many countries. This article presents results obtained so far from ongoing research of published work highlighting water quality monitoring in fishponds. This analysis was performed extensively from May to December 2020 by meticulously selecting a total of 30 internationally published research papers. This review is divided into five categories: (1) recent research (2011–2020), (2) aquaculture environments, (3) research approaches, (4) most common water quality parameters and (5) forms of the solution provided. Most of the published research concentrated on inland aquaculture (81%), while research articles on marine aquaculture species accounted for 19% of papers reviewed so far. The framework and architecture approach (48%) was the most widely practised research approach in IoT‐based aquaculture for water quality monitoring. There is a need for long‐term experimental research to identify the challenges and suggest appropriate solutions. With regards to water quality parameters, temperature (20%), dissolved oxygen (18%) and pH (17%) are the topmost prioritised water quality parameters considered in the IoT‐based aquaculture. Finally, real‐time monitoring (50%) is offered generally as a form of a solution while autonomous (3%) monitoring can be a unique solution. The findings from this study are expected to support the aquaculture industry, researchers, practitioners and decision‐makers in the long run.