Internet of Things (IoT) for Environmental Monitoring

Abstract

Purpose: The general objective of this study was to explore the Internet of Things for environmental monitoring. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to the Internet of Things for environmental monitoring. Preliminary empirical review revealed that IoT technologies have significantly enhanced environmental management practices by revolutionizing data collection and analysis across various ecosystems. By integrating IoT sensors with existing monitoring frameworks, real-time data on air and water quality, agriculture, wildlife habitats, and urban green spaces was efficiently gathered. This data facilitated proactive decision-making, early detection of environmental risks, and evidence-based policy formulation to address climate change, biodiversity conservation, and sustainable resource management challenges. Despite challenges like data security and interoperability, collaborative efforts among stakeholders paved the way for more effective environmental monitoring and sustainable development initiatives globally. Unique Contribution to Theory, Practice and Policy: The Complex Adaptive Systems Theory, Diffusion of Innovations Theory and Resource Dependence Theory may be used to anchor future studies on the Internet of Things technology. The study provided several recommendations that contributed significantly to theory, practice, and policy in environmental management. The study emphasized interdisciplinary approaches to enhance theoretical frameworks, advocating for advanced models and algorithms integrating IoT with environmental science and data analytics. In practice, it recommended widespread adoption of IoT-enabled sensor networks with enhanced capabilities for precise and reliable data collection. Policy-wise, the study called for regulatory frameworks supporting IoT integration, data standards, and international cooperation to address global environmental challenges collaboratively. Capacity building and continuous research and development were also highlighted to optimize IoT technologies for sustainable environmental monitoring and management globally.