This book provides insights into IoT, its applications, and various implementation techniques. The authors first discuss the IoT design methodology to define the domain model. They then cover various connection methodologies used in IoT such as Ethernet, Wi-Fi, low powered wide area network (LPWAN), Bluetooth, RFID, cellular, and satellite, and more, along with their challenges. An example is made on the designing process using Arduino, which offers smart, connected, and secure elements; they also illustrate the integration of IoT with Blockchain, cloud, machine learning, big data, embedded software, sensors, etc. The book going on to cover the future of IoT in various sectors and how IoT will continue to be game-changing technology.

Machine learning (ML) and the internet of things (IoT) are the top technologies used by businesses to increase efficiency, productivity, and competitiveness in this fast-paced digital era transformation. ML is the key tool for fast processing and decision making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. IoT technology has proven efficient in solving many real-world problems, and ML algorithms combined with IoT means the fusion of product and intelligence to achieve better automation, efficiency, productivity, and connectivity. The Handbook of Research on Machine Learning-Enabled IoT for Smart Applications Across Industries highlights the importance of ML for IoT’s success and diverse ML-powered IoT applications. This book addresses the problems and challenges in energy, industry, and healthcare and solutions proposed for ML-enabled IoT and new algorithms in ML. It further addresses their accuracy for existing real-time applications. Covering topics such as agriculture, pattern recognition, and smart applications, this premier reference source is an essential resource for engineers, scientists, educators, students, researchers, and academicians.

Internet of Things (IoT) is a recent technology paradigm that creates a global network of machines and devices that are capable of communicating with each other. Security cameras, sensors, vehicles, buildings, and software are examples of devices that can exchange data between each other. IoT is recognized as one of the most important areas of future technologies and is gaining vast recognition in a wide range of applications and fields related to smart homes and cities, military, education, hospitals, homeland security systems, transportation and autonomous connected cars, agriculture, intelligent shopping systems, and other modern technologies. This book explores the most important IoT automated and smart applications to help the reader understand the principle of using IoT in such applications.

Integration of IoT with Cloud Computing for Smart Applications provides an integrative overview of the Internet of Things (IoT) and cloud computing to be used for the various futuristic and intelligent applications. The aim of this book is to integrate IoT and cloud computing to translate ordinary resources into smart things. Discussions in this book include a broad and integrated perspective on the collaboration, security, growth of cloud infrastructure, and real-time data monitoring. Features: Presents an integrated approach to solve the problems related to security, reliability, and energy consumption. Explains a unique approach to discuss the research challenges and opportunities in the field of IoT and cloud computing. Discusses a novel approach for smart agriculture, smart healthcare systems, smart cities and many other modern systems based on machine learning, artificial intelligence, and big data, etc. Information presented in a simplified way for students, researchers, academicians and scientists, business innovators and entrepreneurs, management professionals and practitioners. This book can be great reference for graduate and postgraduate students, researchers, and academicians working in the field of computer science, cloud computing, artificial intelligence, etc.

The fusion of AI and IoT enables the systems to be predictive, prescriptive, and autonomous, and this convergence has evolved the nature of emerging applications from being assisted to augmented, and ultimately to autonomous intelligence. This book discusses algorithmic applications in the field of machine learning and IoT with pertinent applications. It further discusses challenges and future directions in the machine learning area and develops understanding of its role in technology, in terms of IoT security issues. Pertinent applications described include speech recognition, medical diagnosis, optimizations, predictions, and security aspects. Features: Focuses on algorithmic and practical parts of the artificial intelligence approaches in IoT applications. Discusses supervised and unsupervised machine learning for IoT data and devices. Presents an overview of the different algorithms related to Machine learning and IoT. Covers practical case studies on industrial and smart home automation. Includes implementation of AI from case studies in personal and industrial IoT. This book aims at Researchers and Graduate students in Computer Engineering, Networking Communications, Information Science Engineering, and Electrical Engineering.

This book provides a valuable combination of relevant research works on developing smart city ecosystem from the artificial intelligence (AI) and Internet of things (IoT) perspective. The technical research works presented here are focused on a number of aspects of smart cities: smart mobility, smart living, smart environment, smart citizens, smart government, and smart waste management systems as well as related technologies and concepts. This edited book offers critical insight to the key underlying research themes within smart cities, highlighting the limitations of current developments and potential future directions.

Developing countries are persistently looking for efficient and cost-effective methods for transforming their communities into smart cities. Unfortunately, energy crises have increased in these regions due to a lack of awareness and proper utilization of technological methods. These communities must explore and implement innovative solutions in order to enhance citizen enrollment, quality of government, and city intelligence. IoT Architectures, Models, and Platforms for Smart City Applications provides emerging research exploring the theoretical and practical aspects of transforming cities into intelligent systems using IoT-based design models and sustainable development projects. This publication looks at how cities can be built as smart cities within limited resources and existing advanced technologies. Featuring coverage on a broad range of topics such as cloud computing, human machine interface, and ad hoc networks, this book is ideally designed for urban planners, engineers, IT specialists, computer engineering students, research scientists, academicians, technology developers, policymakers, researchers, and designers seeking current research on smart applications within urban development.

Doctoral Thesis / Dissertation from the year 2019 in the subject Computer Science - IT-Security, grade: 87 %, Bharathidasan University, language: English, abstract: Internet of Things (IoT) and Cloud Computing play a vital role in the field of Information Technology. The goal of IoT is to link objects of heterogeneous in nature to avail smart services and application anywhere, anytime using any device. Cloud Computing allows computer users to conveniently rent access to fully featured applications, to software development and deployment environments, and to computing infrastructure assets such as network-accessible data storage and processing with its salient features of on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured service. Though the Cloud and IoT have emerged as independent technology, merging these two technologies brings renaissance in the field of future networks and in building smart environment. This new evolvement is known as CloudIoT. One of the important challenges in CloudIoT is security. Challenges on the integration of the Cloud within IoT are to be a major bottleneck. The integration of security mechanism and data privacy are also a major concern. Any leakage of information from any of the CloudIoT could severely damage the privacy and authenticity of the users and data. Researchers all over the world put on efforts in integrating smart CloudIoT services to satisfy the needs of the CloudIoT Users. But no prominent architecture has been authenticated so far. Hence, it is imperative to design architecture to integrate CloudIoT smart services and applications to access smart services in a secured manner at anywhere, anytime. The major challenges in implementing this scenario are security factors such as authenticity, confidentiality, integrity, and privacy. In network security, there are several types of attacks which can harm the network resources and services. Distributed Denial of Service (DDoS) is one of the malicious attacks which can harm data communication in CoT potentially. There is a problem that may render customers to withdraw from the cloud services. A traditional DDoS attack aims at servers and/or the bandwidth of a network or a website in order to make them unavailable to their intended users. However, attackers can generate DDoS attack to harm the cloud resources in the same way as the cloud has a huge pool of resources which are larger than attackers resources.

Seminar paper from the year 2017 in the subject Computer Science - Applied, , language: English, abstract: IoT is a revolutionary technology that shows the future of computing and communications and using large scale IoT platforms it is easy to process various number of sensor data. IoT refers to network of objects with wireless technology. IoT platforms are used to process ,analyse the data and produce smart solutions in a short time. This article is to put transmission between wireless sensors and internet for smart agriculture. GPS, RFID,3G, GPRS, geomactics , cloud computing are included with the internet of things are to be focused in order to develop Smart Agriculture. Real time detection. By scripting on RaspberryPi, the monitoring system can get the features like humidity, moisture, light , temperature where the sensors like humidity sensor (RHT03) ,soil moisture sensors ,temperature sensors and PIR sensors can be used to detect the changes in moisture, temperature and light conditions in and around the farm and results are obtained and plotted in graphical form based sheets. Big data analyses are performed to maintain best crop, good production and safe farming.

Special topic volume with invited peer-reviewed papers only