Abstract
Healthcare systems globally face escalating challenges in delivering efficient services while mitigating environmental impact. The integration of Internet of things (IoT) technology offers a promising avenue to address these challenges by fostering sustainability within healthcare ecosystems. This abstract presents an overview of the role and potential impact of IoT in promoting sustainability within the healthcare sector. IoT-enabled devices and sensors offer the capability for real-time monitoring and data collection, facilitating optimized resource utilization and operational efficiency. Through remote patient monitoring, IoT contributes to reducing the carbon footprint associated with frequent hospital visits by enabling remote care and minimizing unnecessary transportation. Furthermore, IoT systems in healthcare infrastructure aid in the efficient management of energy consumption, optimizing resource allocation for lighting, temperature control, and equipment usage. This results in significant decreases in energy usage and the emission of greenhouse gases. Moreover, the implementation of IoT in healthcare supply chains enables enhanced inventory management, minimizing waste through precise tracking of pharmaceuticals, medical supplies, and equipment. This streamlined approach reduces overstocking, prevents expiration of medicines, and minimizes unnecessary disposal, thereby promoting sustainability. IoT-generated data analytics provide insightful information on healthcare procedures, enabling well-informed decision-making to optimize workflow, enhance patient care, and reduce waste production. The multifaceted role of IoT in fostering sustainable practices within healthcare systems and leveraging IoT technology not only enhances operational efficiency but also significantly reduces the environmental impact of healthcare operations, contributing to a more sustainable future.
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Chirchi, V., Chirchi, K.E., Chirchi, E. (2024). IoT for Health Care: A Sustainable Approach. In: Devi, V.A. (eds) Sustainable IoT and Data Analytics Enabled Machine Learning Techniques and Applications. Contributions to Environmental Sciences & Innovative Business Technology. Springer, Singapore. https://doi.org/10.1007/978-981-97-5365-9_6
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DOI: https://doi.org/10.1007/978-981-97-5365-9_6
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