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This book brings together the latest research in smart sensors technology and exposes the reader to myriad industrial applications that this technology has enabled. The book emphasizes several topics in the area of smart sensors in industrial real-world applications. The contributions in this book give a broader view on the usage of smart sensor devices covering a wide range of interdisciplinary areas like Intelligent Transport Systems, Healthcare, Agriculture, Drone communications and Security.
By presenting an insight into Smart Sensors for Industrial IoT, this book directs the readers to explore the utility and advancement in smart sensors and their applications into numerous research fields. Lastly, the book aims to reach through a mass number of industry experts, researchers, scientists, engineers, and practitioners and help them guide and evolve to advance research practices.




Sensors play a crucial role in capturing the measurements from the environment around and on computation produced results for further understanding and analysis of the environment. Sensors are vital for applications in a broad range of industrial operations. The book on Smart Sensors for Industrial Internet of Things brings together the latest research in smart sensors technology and exposes the reader to myriad industrial applications that this technology has enabled. The contributions in this book give a broader view of the usage of smart sensor devices covering a wide range of interdisciplinary areas like Intelligent Transport Systems, Healthcare, Agriculture, Drone Communications, and Security. By presenting an insight into smart sensors for industrial IoT, this book directs the reader to explore the utility and advancements in smart sensors and their applications into numerous research fields.
Deepak Gupta, Victor Hugo C. de Albuquerque, Ashish Khanna, Purnima Lala Mehta

Internet of Things Concept and Its Applications

In the current era of digital communication and networking, the term Internet of Things abbreviated as IoT has become very famous. The Internet of Things relates essentially to the network interface and communication of physical objects, devices, and peripherals that can interact and exchange data between one another without depending on human interactions or computer interactions. IoT applications promise to add enormous value to our lives. With newer wireless networks, superior sensors, and revolutionary computing capabilities, for its wallet share, the Internet of Things could be the next frontier in the race.
Prashant Ahluwalia, Nitin Mittal

Smart Sensors and Industrial IoT (IIoT): A Driver of the Growth of Industry 4.0

Smart sensors and Industrial Internet of Things (IIoT) are innovative tools in the current business environment and are considered drivers of Industry 4.0, as well as factories, households, and workplaces. Using smart sensors in a variety of ways, companies can improve and grow their business (Bahrin, M.A.K., Othman, M.F., Azli, N.N., Talib, M.F.: Industry 4.0: a review on industrial automation and robotic. J. Teknol. 78(6–13), 137–143 (2016)). In the current business environment, it has been seen that smart sensors act as catalysts and drivers for taking a company to the top of its industry. The use of smart sensors and IIoT in business practices in various sectors of the economy has a very positive impact on delivering value and quality products and services, and it also helps in reducing costs, increasing production output, and enhancing efficiency.
The combination of smart sensors and IIoT represents the ordering and arrangement of a sensor, microprocessor, and communication technology for the purpose of converting environmental inputs (e.g., humidity, weight, liquid detection, temperature) into readable data and transmitting the data to a centralized repository.
Once implemented at scale, the combination of sophisticated sensors and increased computational power will enable new ways to analyze data and gain actionable insights to improve many areas of operations.
In this chapter, the author will present an analysis of changes initiated by applying smart sensors and IIoT in industry to connect technologies in industries, factories, households, and workplaces. The objective of this chapter is to seek answers to the question of how smart sensors and IIoT act as innovative tools driving growth in the current business environment and to explore the role and significance of smart sensors and IIoT in daily life and, most importantly, in business and manufacturing. The author will also try to analyze the impact of smart sensors and IIoT on operations in manufacturing or business organizations and discuss smart sensors so as to arrive at a better understanding of the underlying reasons why both producers and consumers are resistant to smart products.
Vijay Prakash Gupta

Smart Sensors for IIoT in Autonomous Vehicles: Review

Autonomous vehicle is designed to perform all various operations synchronously to work under necessary regulations, liability, acceptance, and safety with Industrial IoT. The autonomous vehicle mainly works with three sensors, such as Camera, RADAR, and LIDAR. These sensors gather the information data like image, distance, waves and provide it to the electronic controllers, where it processes to take the appropriate actions. During the processing of the information, various parameters, such as latency, packet loss, and bandwidth, are evaluated using the historical and available information. The information data generated by the sensors are processed using various signal conditioners to meet the required parameters. In this chapter, some of the signal conditioning methods, such as RF module, BTS, TPMS, and capacitive balancing of humidity sensor (in HVAC), are used in autonomous vehicle and Industrial IoT implementation. The communication modes and their aspects from Industrial Internet of Things are discussed and existing methods for the systems are analyzed from the signal conditioning perspective.
Suresh Chavhan, Ravi Arun Kulkarni, Atul Ramesh Zilpe

Vehicular Intelligence: A Study on Future of Mobility

IoT is redefining the way we look at things today. “Things” today are able to communicate and with AI being deployed at the edge, a whole new window of possibilities has opened up. Things with communication capabilities which we called Intelligent Internet of Things are able to bring transformations to healthcare, manufacturing, transportation, automobiles, and many other industries in many ways. Connected vehicles is one outcome of the IoT and intelligence of edge devices which is bringing infotainment, remote diagnosis, entertainment, automatic braking, lane detection, collision avoidance and lot of other systems that are being helpful in increasing the passenger safety, pedestrian safety and at the same time decreasing congestion, traffic delays as a result of which reducing the effect environmental pollution due to over burning of fuel during congestion. Road accidents today are one of the top ten reasons of human death according to various reports. In this kind of scenario, connected vehicle technology along with intelligent traffic system can help a lot in increasing the safety of people on road.
Anish Kumar Sarangi, Ambarish Gajendra Mohapatra

Connected Vehicles: Intelligent Transport Systems

The world so far has witnessed an exponential growth of vehicle on road. With the increase in the number of vehicles, there are evidently a large number of problems encountered on the road. Some of these problems could be named as populated and polluted roads, violation of traffic rules, road accidents, excessive wastage of fuel, delay in emergency services, etc. The proposed work intends to alleviate these problems by designing a long-range decentralized network of vehicles. All the vehicles within the range of a kilometer will be able to communicate with each other to solve all the specified problems. The major focus of the work will be on designing a secure network within the range of a few hundred meters. A specified code word will be broadcasted from each vehicle in such a way that there occurs no data collision between transmissions from different vehicles. First and foremost the transmitted code will specify if the vehicle is facing an emergency situation or not. The additional information in the code will include the address of the vehicle in network, checksum, and parity to ensure accurate transmission of data.
Navneet Yadav, Rama Kanta Choudhury

Design of Auto-Braking System for Accident Prevention and Accident Detection System Using IoT

In recent times, frequencies of accidents have increased considerably. This is because of an increase in the number of vehicles, carelessness of drivers, and over speeding. Over speeding is the main reason for increase in the number of accidents. In this work, the primary concern is to decrease the impact of collision, and after that communicating with the nearby hospital for providing necessary support to the victims. According to data provided by the Ministry of National Highway, most of the deaths occurred because of not getting help in crucial times or not getting an ambulance service in time. Our main aim is to communicate with the nearest hospital through GPS and help the victims. Our work is divided into two main parts. One is sensing and communication part. Other is the braking part which has three steps. When the distance of the vehicle from the obstacle is more than 30 m then the system is disabled. If the distance becomes less than 30 m then a warning is generated by the system for the driver to apply brakes. If the distance is further reduced and becomes less than 4 m understanding that the driver has lost control over the vehicle, control is fully transferred to the braking system and plugging braking is used to stop the vehicle instantly to reduce the impact of a possible collision.
Gitanjali Mehta, Manoj Singh, Shubham Dubey, Uzair, Yogesh Mishra

IoMT with Cloud-Based Disease Diagnosis Healthcare Framework for Heart Disease Prediction Using Simulated Annealing with SVM

Internet of Medical Things (IoMT) interlinks a collection of intelligent sensors on the patient’s body to observe and interpret multimodal health data, including the patient’s physiological and psychological signals. The large amount of data produced by IoMT devices in medical application is examined on cloud by replacing the restricted memory as well as processing resources of handheld tools. In this study, an IoMT-based healthcare diagnosis model is introduced by the use of intelligent techniques. This paper proposes a new IoMT-based disease diagnosis healthcare framework for heart disease prediction using the BBO-SVM model. The proposed model involves the parameter tuning of SVM using the BBO algorithm. The validation of the proposed model takes place using a Statlog Heart disease dataset. The detailed experimental analysis strongly pointed out that the proposed BBO-SVM model has shown excellent results by attaining a maximum precision of 88.33%, recall of 87.60%, accuracy of 89.26%, F-score of 87.96%, and kappa value of 78.27%.
Kishore Kumar Kamarajugadda, Pavani Movva, Manthena Narasimha Raju, S. Anup Kant, Satish Thatavarti

Hyperparameter Optimization of Deep Neural Network in Multimodality Fused Medical Image Classification for Medical and Industrial IoT

Industrial Internet of Things (IIoT) refers to the extension and utilization of the Internet of Things (IoT) in industrial sectors and applications. Medical image fusion and classification has been utilized to get valuable significant multimodality medical image data. Recently, deep learning methods offer an effective way to design an end-to-end model that can determine the final classification labels. This chapter introduces a Multimodality Image Fusion Classification (MMIFC) by the incorporation of image fusion, feature extraction, and classification techniques. Initially, the input medical images were fused by the use of optimal shearlet transform where the coefficients of shearlets are optimized by the use of Enhanced Monarch Butterfly Optimization (EMBO) algorithm. In the next stage, the fused images were classified based on the feature extractor and deep learning model to check the test image is malignant and benign. To further optimize the performance of the deep learning model, hyperparameter tuning process takes place by the use of Bayesian optimization model to optimize the weights of structure. Finally, this ODNN model classifies the MMFI as class 1 or 0. A detailed simulation result takes place to ensure the effective performance of the proposed method. From the experimental results, the proposed strategy accomplishes better fusion rate and classification results compared with other supervised and non-supervised learning techniques.
Velmurugan Subbiah Parvathy, Sivakumar Pothiraj, Jenyfal Sampson

Cognitive IoT-Based Smart Fitness Diagnosis and Recommendation System Using a Three-Dimensional CNN with Hierarchical Particle Swarm Optimization

Due to the worldwide increase in economic development, fitness centers are rising quickly all over the globe. In this view, people require methodical and realistic supervision for building their body. At the same time, Cognitive Internet of Things (CIoT) is capable of learning, sensing, decision-making, and transferring intelligence to humans. Recently, several methods have been evolved to address the fitness and health, where the wearable fitness models let down the market rate. In this paper, a Cognitive IoT-Based Smart Fitness Diagnosis and Recommendation System using a three-dimensional convolutional neural network (CNN) with hierarchical particle swarm optimization (PSO) algorithm has been presented. The proposed model is applied to observe the health statuses of exercisers. The system offers proper supervision to the exercisers. A set of experiments takes place, and the simulation results highlight the betterment of the proposed model.
Chalumuru Suresh, M. Ravikanth, B. Srivani, Thatavarti Satish

Industrial Internet of Things (IIoT) with Cloud Teleophthalmology-Based Age-Related Macular Degeneration (AMD) Disease Prediction Model

Industrial Internet of things (IIoT) utilizes smart sensors and actuators for enhancing manufacturing and industrial processes. Due to the advanced technological developments in healthcare industry, it has been proved that the primary detection of chronic diseases, namely, diabetic retinopathy (DR) as well as age-related macular degeneration (AMD), is capable of preventing loss of vision. In this study, a scalable cloud-oriented teleophthalmology structure by an Internet of medical things (IoMT) to detect AMD is projected. In the presented system, patient’s wearable camera for transmitting the retinal fundus photographs for a secured cloud drive storage for diagnosing the severity of disease as well as predictive progression examination. A projected optimal generative adversarial network (OGAN) helps to investigate the images to find as well as to compute AMD disease severity. The GAN would be optimized with the application of a bat method. The performance of the proposed OGAN model has been validated using a set of benchmark images. A set of three measures used to examine the results are sensitivity, specificity, and accuracy. The experimental outcome showed the superior performance of the proposed model over the compared methods by attaining a maximum accuracy of 98.03%.
R. J. Kavitha, T. Avudaiyappan, T. Jayasankar, J. Arputha Vijaya Selvi

Significance of IoT in the Agricultural Sector

Agriculture has a crucial role to play in the overall growth of an agricultural nation. In our country, around 70% of the population are dependent on irrigation, while about one-third of the country’s revenue is derived from agriculture. The situation pertaining to farming has always been an obstacle in a country’s growth. The agricultural sector is boosting with the introduction of information and communication technology in this sector. Efforts are being made to enrich productivity and to decrement the cost of expenditure by utilizing the state-of-the-art technology and equipment. A feasible solution to this issue is smart agriculture by revolutionizing present-day conventional techniques of farming. To enhance effectiveness, productivity, and world market and to reduce manual labor, latency, and expenses, there is a necessity to divert toward the Internet of Things which will be gaining popularity in the coming years’ time. IoT is the network of interconnected devices to transfer the sensed data without human involvement. Hence, to achieve high productivity, IoT in synergy with agriculture will provide smart farming. Our study in this chapter deals with various issues and scope of IoT technology in the agricultural domain. Various challenges concerning smart agriculture are presented in this chapter. Later a smart IoT-based architectural system model is illustrated and discussed in detail. Its implementation with its benefits is also presented with clarity.
Sushruta Mishra, Pradeep Kumar Mallick, Debjit Koner

Soil Moisture Sensor Nodes in IoT-Based Drip Irrigation System for Water Conservation

Agricultural data analysis is an important challenge for the data mining community present not only in India but also in the world. This is due to the fact that majority of the cultivation lands in the globe suffer highly from shortage of irrigation water. In such a scenario, drip irrigation techniques have been developed by researchers to reduce the water consumption in dry areas. However, due to the lack of guidelines and systematic techniques to utilize the water and electricity in an optimistic manner, the agricultural sector faces water problem in many places. Therefore, the overheads of farmers using the conventional drip irrigation have become high, and they have to manually visit and monitor the lands frequently. Agricultural data can be collected more efficiently by the use of sensors for data collection and also for effective analysis. A smart irrigation system can be built with smart sensor networks for collecting field values and can be analyzed using rules for effectively watering the plants. Hence, a new sensor network-assisted irrigation system and rule-based analysis model have been developed in this research work to enhance the efficiency of water usage.
K. Muruganandam, Usha Chauhan

Precision Agriculture Using Advanced Technology of IoT, Unmanned Aerial Vehicle, Augmented Reality, and Machine Learning

Agriculture is one of the primary processes for quality food production in the globe. Unfortunately, the productivity of agriculture is very low, and many factors affect the yield level of it. Precision agriculture (PA) is one of the solutions for the above problem. PA uses site-specific crop management concept based on measured data using sensors and data analytics to find the root cause of yield reduction. Precision agriculture automates farming which involves the collection of data and analysis of them for better decision-making to gain high yield and quality of the agricultural product. The agriculture system integrated with data analytics and machine learning is called as smart farming or smart agriculture The goal of smart agriculture is to develop a decision-making support system for farming management. The precision smart agriculture can be enhanced with the help of latest technologies of Internet of Technology (IoT), unmanned aerial vehicle (UAV), augmented reality (AR) system, and machine learning (ML) algorithms. This chapter focuses on the illustration and utilization of those advanced technologies for smart farming.
Vijayakumar Ponnusamy, Sowmya Natarajan

IoT-Based Brinjal Crop Monitoring System

Many real-time applications perceive the various advances made in numerous domains using new technologies. Still, the use of these new innovations in the agricultural sector remains a challenging task. This paper uses a remote crop monitoring mechanism using LoRaWAN in the greenhouse. The motive of this paper is to enhance the traditional way of agriculture in rural areas with the help of a wireless sensor network using LoRaWAN protocol. This paper proposes a design and implementation of a system having an IoT-based sensor that senses the temperature of the environment inside the greenhouse for brinjal with the aim to control the devices like fan and heater according to the optimal range for food production and proper growth of the crop. The proposed model is implemented and validated using the CupCarbon simulator. The results show that our approach is fast and that this model provides shorter simulation time with greater efficiency.
Navdeep Kaur, Gaurav Deep

Internet of Drones: An Engaging Platform for IIoT-Oriented Airborne Sensors

Internet of things, since its conception in the year 2000, has been steadily permeated in almost every sector that humans have created till now, which includes industry, business, entrepreneurs, academia, and so on. The impact is so high that IoT is now creating a paradigm shift for an overall ecosystem. Besides any other form, in which IoT may be playing its part, Internet of drones (IoD) is a recent yet greatly appreciated and rapidly incorporated form. Being an aerial vehicle, IoD provides extreme reachability for any IoT devices under operation, and for that reasons, various stakeholders and business consider it as pivotal for their needs. IoD is now being explored for its feasibility and operability scenarios, where it can cascade to existing drone operations. This chapter shall take a walk on describing IoD and proposes state-of-the-art architecture and it’s applications, especially those that are oriented to industrial IoT.
Ambuj Kumar, Purnima Lala Mehta

A Novel Approach on Renewable Energy Harvesting Using Internet of Things (IoT)

The goal of this undertaking is to audit existing sustainable power source and imminent methodologies in vitality reaping procedure as methods for having an economical and low support activity of WSN (wireless sensor networks). The Internet of Things idea has been utilized to build up the undertaking. Sunlight-based vitality reapers are getting to be basic in home and structures to give considerable advantages to our atmosphere, well-being, and economy. It together with other inexhaustible sources will soon outdate the customary fossil vitality to turn into a column for economical improvement. An IoT-based system is implemented to distribute energy among the solar board. The power gathered by sunlight-based clusters, in any case, relies on different factors, for example, climate conditions, photovoltaic (PV) boards, and vitality transformation that need broad and constant examinations to boost its potential. In the primary bearing, fixed, single, and twofold pivot trackers are created to follow the course of the sun. An electromechanical framework to pursue the situation of the sun was structured. It is coordinated by a shut circle servo framework that takes estimations of direct sun-based radiation as the criticism. The control methodology is to drive two little dc engines with the goal that the sun picture is kept at the focal point of the four-quadrant photograph indicator detecting the sun position.
S. Chandragandhi, E. Udayakumar, K. Srihari

Security and Surveillance at Smart Homes in a Smart City Through Internet of Things

Smart home infrastructure consists of intelligent networking devices, infrastructure, and seamless integration of various devices using wired/wireless technologies. It allows the ease of use for household systems and creates a highly personalized and safe home space. There are many corporates that are seriously indulging in smart home systems which include GE, Cisco, Google, Microsoft, and others. Smart homes provide a productive and cost-efficient environment and maximize the effectiveness of the occupants. Smart homes provide efficient management with minimum life-time costs of hardware and facilities. They optimize the things such as structures, systems, and services and also manage the interrelationships between these three. The present research focuses on how security and surveillance are achieved in smart homes.
Rinky Dwivedi, Koyel Datta Gupta, Deepak Sharma


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