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Full Description
Internet of Things (IoT) is a new platform of various physical objects or "things” equipped with sensors, electronics, smart devices, software, and network connections. IoT represents a new revolution of the Internet network which is driven by the recent advances of technologies such as sensor networks (wearable and implantable), mobile devices, networking, and cloud computing technologies. IoT permits these the smart devices to collect, store and analyze the collected data with limited storage and processing capacities.
Swarm Intelligence for Resource Management in the Internet of Things presents a new approach in Artificial Intelligence that can be used for resources management in IoT, which is considered a critical issue for this network. The authors demonstrate these resource management applications using swarm intelligence techniques. Currently, IoT can be used in many important applications which include healthcare, smart cities, smart homes, smart hospitals, environment monitoring, and video surveillance. IoT devices cannot perform complex on-site data processing due to their limited battery and processing. However, the major processing unit of an application can be transmitted to other nodes, which are more powerful in terms of storage and processing. By applying swarm intelligence algorithms for IoT devices, we can provide major advantages for energy saving in IoT devices. Swarm Intelligence for Resource Management in the Internet of Things shows the reader how to overcome the problems and challenges of creating and implementing swarm intelligence algorithms for each application
Contents
1. Swam intelligent based Internet of Things affect E-Governance for corporate governance to facilitate firm performance: A holistic approach
2. Swarm Intelligence-based Buildings Energy Management Systems for IoT Applications
3. Swarm intelligence algorithms and their applications in Internet of Things (IoT)
4. Energy management based on Internet of Things
5. Swarm Intelligence as a Solution for Technological Problems associated with IoT
6. Arbitrary Walk with Minimum Length Based Route Identification Scheme in Graph Structure for Opportunistic Wireless Sensor Network
7. Revolutionizing Internet of Things with Swarm Intelligence
8. Machine Learning techniques optimized by Practical Swarm optimization for Intrusion Detection in IoT
9. Cyber-Physical Systems in Smart City: Challenges and Future Trends for Strategic Research
10. Swarm Intelligence for routing of Internet of Vehicles (IoV)
11. A New Swarm-Intelligence Framework for Internet of Medical Things System in healthcare
