Buildings consume nearly one-third of global energy and are responsible for one-fourth of CO2 emissions, thereby playing a crucial role in polluting the earth. Cities are more vulnerable as there are more buildings and a huge population due to employment opportunities. Hence, there is a need for the transformation of cities into smart cities with viable environments by making buildings smart. Smart cities with energy-efficient buildings can improve the economy and reduce pollution effects, thereby improving the quality of city life. As human errors and carelessness jeopardise energy conservation and eco-friendly initiatives in traditional buildings, automatic internet of things (IOT) monitored building control, also known as a smart building, is a need of the hour if the world is to advance toward smart cities. The management of the cities should estimate their energy consumption in advance and plan strategies that will help in reducing the energy consumption of both commercial and residential buildings towards creating a pollution-free smart city. The IOT sensors produce continuous streaming data, which necessitates big data analysis to improve the performance of building in terms of energy consumption. Big data analysis based on machine learning techniques is currently being employed for such an automatic analysis and management of buildings based on IOT sensor data. This chapter focuses on bringing out the commercially available IOT sensors for collecting building data, their efficiencies, extracted features and the commonly used machine learning techniques, their strengths, and drawbacks and also identifies the research gap and work to be done for further improving big data analysis of smart energy management.

 Energy and the environment have both become a matter of concern among researchers worldwide. There are several forms of energy present in the environment; therefore, utilizing these resources is preferred. In the modern world, the evolution of energy harvesting has received a lot of attention. Various energy harvesting topologies like solar, vibrational, piezoelectric, RF (radio frequency), etc., are available, but RF energy harvesting has a bright future in generating a small amount of electric power that drives various power-constrained electronic devices due to its easy availability and self-sustainability. The circuitry, which converts RF energy into DC output, is termed the rectenna unit of the model. The rectenna unit consists of receiving antenna followed by the matching network and rectifier. The aim of this chapter is to provide a detailed review of various technical aspects of radio frequency energy harvesting, which have been showing a great proliferation in the designing of the RF energy harvesting model. Comparative analysis of different topologies of each aspect is also performed.

An intelligent transportation system (ITS) is a well-developed program that aims to provide innovative assistance in identifying various methods of transportation and traffic management. It is empowering clients to be better educated and make more secure, increasingly prepared, and 'more intelligent utilization of transport systems. Internet of Vehicles (IoV) is a rising idea in ITS to upgrade the current abilities of Vehicular Ad-hoc Networks by incorporating them into the Internet of Things. IoV has commanded the vehicular frameworks because of various exceptional characteristics like dominant topographic network structures, massive network proportion, consistent internet connection, a similarity of individual gadgets, and elevated handling ability. An intelligent transportation framework includes a gigantic measure of transforming real-time critical information, in which security plays a significant part. In this chapter, an investigation of IoV and VANETs has been conducted, with distinctive security aspects of IoV being emphasized, incorporating security requirements, security risks, and security attacks. Finally, persisting current lightweight cryptographic security solutions for IoV related attacks are summarized. 

 Due to technological advancements, people are migrating to urban areas for better health care, employment, amenities, and education. Communication technology innovations are going to play a crucial role in smart cities. These technologies are the heart and brain of the smart city. In this chapter, various technologies like IoT and cyber-physical systems (CPS) have been discussed. Security challenges for IoT and CPS are pointed out in this chapter, and solutions to these challenges are also suggested.

In recent decades, more people inhabit cities than rural areas, due to the increase in population, change of climate, and shortage of resources. Many countries are emphasizing the transformation of the city into a smart city for the effective utilization of the opportunities of urbanization. Today, smart cities are one of the thrust areas of many governments across the globe. Smart cities are being planned to promote a pollution-free environment and facilitate smart infrastructure. To enable operational efficiencies and to achieve sustainable economic growth in smart cities, innovative technologies are necessary. This book chapter focuses on the current urban challenges arising during the management of smart cities. It discusses one of the vibrant technologies – blockchain technology and its usage for the management of smart cities. Further, it explores the current scenario of global blockchain technology initiatives. It studies various domains of a smart city and also recognizes the domain where blockchain technology can be implemented for better livability and development of cities. Also, it focuses on the various use cases of blockchain in developing the smart city. Finally, it explains the practical feasibility for the successful implementation of blockchain technology briefly. 

The modern Era is a boon to humanity with ever-changing technology, which makes it possible to do the things that can make our world smart and sustainable. God is a great creator, and along with so many variations, he has also created people with a unique abilities. Accidently or eventually, due to old age, a healthy person may be helpless and then suffer from depression due to sustainability issues in this fastmoving and emotionless world. However, with cognitive computing technologies and machine learning, Artificial Intelligence (AI) is a miracle specifically in the form of Virtual Personal assistants. Many instances are available in the recent literature about the same. This chapter presents a simple, mobile-based user-friendly application that can be operated with a multi-lingual voice signal to enable the person to perform regular tasks. This concept gives an intelligent platform to automate our tasks with ease, comfort, and accuracy. The idea of a smart and sustainable world motivated us to develop a Personal Helper with brilliant intelligent powers, interacting with the objects in our surroundings, mobile services, and PC services just by one human voice. The hardware device receives the audio request through a voice input device like a microphone. The proposal is then processed so that the device can execute the task. The primary objective of the virtual assistant is to help the disabled, specially-abled people, do their work by giving single voice commands in their natural voice. The chapter demonstrates the concept of significantly reducing impaired or elderly persons' physical efforts and living a 'smart' quality life.

Rice is the staple food crop of a large population spread worldwide, today and in the past. Millions of people are dependent on rice for an active and healthy lifestyle. A smart and sustainable world is a pictograph that will come into reality with an abundance of quality food for humankind. Smart precision agriculture leading to the fulfillment of high-quality food is a challenge for many researchers. In the same series of thoughts, this chapter proposes a Smart App using Deep Learning that helps diagnose the rice crop disease to avoid failure of the crop. This chapter demonstrates an easy to handle, farmer-friendly mobile app, with the help of which farmers can take pictures of crop leaves as soon as some abnormality is observed. The app may then analyse the crop leaf image to predict the probability of suspected disease, which gives the farmer indication of loss and helps them take necessary preventive measures.

Clean and healthy environmental maintenance is very important for sustainable development. Prevention and reduction of pollution, and reuse, and recycling of materials are some of the best practices of environmental management. Environmental monitoring is a systematic method of sampling air, water, soil and biota and assessing their quality and characteristics. The environmental monitoring process includes establishing a baseline of exposure, correlating with contamination source, estimating concentration changes of pollutants and extracting the information from collected data. This information can be used as input for the design of treatment plants; to check for compliance with standards, preventive measures of hazards, etc., the monitoring methods are categorized as ground-based sampling and measurements, a simulation model-based monitoring, and satellite monitoring. Ground-based monitoring provides accurate results, whereas simulation models give prior information about the prediction of pollutant levels, and satellite monitoring details environmental quality over a greater areal extend. Monitoring can also be subdivided into source and ambient environmental monitoring. IoT-based smart environmental monitoring is gaining more attraction nowadays with the advent of technology. It makes the labor-intensive process a simple one. The chapter explains the different IoT components/architectures of monitoring various applications related to air, water, and soil quality. Application of IoT is not only limited to the Sestriere sources but also monitoring of forest fires, analysis, and prediction of climate change patterns, early warning systems of natural disasters, monitoring levels of snowfall, etc. 

In this chapter, metamaterials and their properties in the application of antenna designs are discussed. Although metamaterials offer great benefits in diverse areas, this work emphasizes their implementation in the development of smart cities. The world faces challenges ensued to environmental problems, population growth, and other current dynamics. New technologies are required to present solutions for cities to be organised efficiently and effectively while also supporting the environment by pursuing higher sustainability. Intelligent street lighting systems are one out of the several approaches that offer promising development opportunities. Intelligent street lights have already been implemented in some cities, with positive outcomes in terms of energy savings, reduced traffic, improved infrastructure, and supply, etc. The different concrete goals of a smart city and intelligent streetlight concepts were discussed, and the research on metamaterials was accordingly adapted. At the current state of technology, there are no metamaterial antennas on the market that are directly declared to be suitable for the installation of intelligent streetlights. However, due to the great advantages of metamaterial antennas, it would be worthwhile to look into ways to improve the functionalities of intelligent streetlights using these antennas. In this chapter, the suitability of metamaterial antennas implemented in streetlights is studied. Some existing planar antennas were enhanced by incorporating metamaterials into them. The analysis shows that the radiation performances of the enhanced antennas are significantly improved. Therefore, metamaterial antennas have the potential of being applied in a broad range of applications, including intelligent streetlights.