Internet of Things

Energy, Industry, and Healthcare

Arun Kumar Rana, Ayodeji Olalekan Salau, Sharad Sharma, Shubham Tayal, Swati Gupta, Arun Kumar Rana, Ayodeji Olalekan Salau, Sharad Sharma, Shubham Tayal, Swati Gupta

• Éditeur: CRC Press
• Année: 2021
• ISBN:
  9781000450491
• Édition: 1
• Sujet: Computer Science
• Sous-sujet: Systems Architecture

Internet of things (IoT) is the connection and communication of physical objects (smart devices) over the internet. In this recent age, people's daily lives are dependent on the internet through their smartphones, tablets, Smart TVs, micro-controllers, Smart Tags, computers, laptops, and cars to name a few. This book discusses different ways to create a better IoT network and/or IoT platforms to improve the efficiency and quality of these products and subsequently their users' lives. In addition, this book provides future research directions in energy, industry, and healthcare, and explores the different applications of IoT and its associated technologies. It provides an overview and explanation of the software architecture, middleware, data processing and data management as well as security, sensors, actuators and algorithms used to create a working IoT platform. The editors then go on to examine IoT networks and platforms as they relate to energy industry including, energy efficiency and management, intelligent energy management, smart energy through blockchain and energy-efficient/aware routing/scheduling challenges and issues. They then explore IoT as it applies to healthcare including biomedical image and signal analysis and disease prediction and diagnosis. Finally the editors examine the prospects and applications of IoT for industry through the concepts of smart industry, including architecture, blockchain, and Industry 4.0. This book is intended for senior undergraduate and graduate students, researchers and industry professionals working on IoT applications and infrastructure.

• Reviews IoT software architecture and middleware, data processing and management, security, privacy and reliability, architectures, protocols, technologies, algorithms, and smart objects, sensors, and actuators

• 
  
  

• Explores IoT as it applies to energy, including energy efficiency and management, intelligent energy management, smart energy through blockchain and energy-efficient/aware routing/scheduling challenges and issues Examines IoT as it applies to healthcare including biomedical image and signal analysis, and disease prediction and diagnosis

• 
  
  

• Examines IoT as it applies to smart industry including architecture, blockchain, and Industry 4.0

• 
  
  

• Discusses different ways to create a better IoT network or IoT platform

1 VANET-Based Intelligent Traffic Light Control System by Detecting Congestion Using Fuzzy C-Means Clustering Technique in a Smart City

Anita Mohanty^1,*, Subrat Kumar Mohanty², and Bhagyalaxmi Jena1

¹Silicon Institute of Technology, Bhubaneswar

²College of Engineering Bhubaneswar, Bhubaneswar

DOI: 10.1201/9781003140443-1

1.1 Introduction

Year after year, the traffic density on roads has been rising worldwide due to rapid developments in the automotive industry and improvements in public living standards. This leads to the phenomenon called traffic jams. Traffic jams or traffic congestions have a direct impact on the economy [1] and the environment, and are stressful for motor vehicle drivers as they lead to a waste of time at a junction. To minimize these effects, there is need for developing a novel Intelligent Transportation System (ITS). Conventional traffic detection, control, and monitoring solutions are infrastructure-based. They include video and image processing, inductive loops [2,3], and microwave radars [4]. These methods are capable of providing traffic information of a fixed point or that of a shorter road section. They can detect traffic conditions at a particular location only and might not be able to provide information about traffic conditions over a large road segment. Thus, a Cooperative Vehicular Communication System [5] is considered an important ITS technology in a Vehicular Ad-hoc Network (VANET) to enhance the effectiveness of the system through continuous exchange of information between the vehicle and infrastructure (V2I Communication). VANET is a subtype of a mobile network with vehicles as nodes that run on a road and communicate with one another as well as with infrastructure nodes through wireless technology [6–8]. In this technique, vehicles running on roads help gather information about other nearby vehicles and the possibility of a jam, and alternate the congestion conditions between them. In almost all detection techniques, including a gain amplifier [9], congestion recognition using wavelet technique [10], pattern recognition [11], and the number of messages collected from particular vehicles is large. Because of the limited availability of bandwidth in VANET, a clustering scheme is expected to be developed.

When the vehicles are in a traffic congestion, some of their parameters, such as speed, fuel consumption, and carbon dioxide (CO₂) emission, are very much similar. As these vehicles are in a dynamic state, the most popular clustering method i.e. FCM is preferred for detection of congestion. After detection of a congestion, the traffic jam is dispersed by changing the traffic light sequence as well as the duration of the green light at a junction.

Traffic lights are signaling devices installed at the junction of a road and are used to control the ...