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IoT-Based Decision Support Systems for Smart Environments

Author(s) Dr. Sophia Williams
Country Australia
Abstract IoT-based decision support systems have emerged as an important technological approach for transforming data generated by connected environments into actionable information for intelligent decision-making. The integration of Internet of Things devices, wireless sensor networks, cloud computing, edge computing, artificial intelligence, machine learning, and predictive analytics enables decision support systems to continuously collect, process, interpret, and communicate information from smart environments. This study examines IoT-based decision support systems for smart environments, focusing on sensing architectures, data integration, intelligent analytics, real-time decision support, predictive capabilities, automation, and application domains.
A qualitative descriptive and conceptual research design was adopted using secondary academic literature. The analysis indicates that IoT-enabled decision support can improve situational awareness, resource management, operational efficiency, responsiveness, and predictive decision-making across smart homes, healthcare environments, industrial facilities, agriculture, transportation, energy systems, and smart cities. IoT sensors provide continuous environmental and operational information, while edge computing supports low-latency processing and cloud platforms provide scalable analytical capabilities. Artificial intelligence and machine learning can identify patterns, detect anomalies, forecast conditions, and generate decision recommendations.
Despite these benefits, challenges related to data quality, interoperability, cybersecurity, privacy, system complexity, computational resources, and scalability continue to affect implementation. The study concludes that effective IoT-based decision support requires an integrated architecture combining sensing, communication, intelligent analytics, visualization, and automated or human-centered decision mechanisms. Future research should emphasize explainable AI, secure IoT architectures, edge intelligence, context-aware decision support, interoperable platforms, privacy-preserving analytics, and sustainable smart-environment infrastructures.
Keywords Internet of Things, Decision Support Systems, Smart Environments, Artificial Intelligence, Machine Learning, Edge Computing, Smart Cities, IoT Analytics, Intelligent Decision-Making, Connected Systems
Field Engineering
Published In Volume 5, Issue 1, January-February 2023
Published On 2023-01-27
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