Textbook in PDF format

The book aims to provide a deeper understanding of the relevant aspects of Artificial intelligence (AI) and IoT impacting each other’s efficacy for better output. Readers may discover a reliable and accessible one-stop resource; An introduction to Artificial Intelligence presents the first full examination of applications of AI, as well as IoT presents the smart objects, sensors or actuators using a secure protocol to the Artificial Intelligence approaches. They are designed in a way to provide an understanding of the foundations of artificial intelligence. It examines Education powered by AI, Entertainment and Artificial Intelligence, Home and Service Robots, Healthcare re-imagined, Predictive Policing, Space Exploration with AI, and weaponry in the world of AI. Through the volume, the authors provide detailed, well-illustrated treatments of each topic with abundant examples and exercises.
Chapters are edited by experts in IT and Machine Learning, and are structured to make the volume accessible to a wide range of readers.
Key Features:
- This book contains different topics about the most important areas and challenges in the Internet of Things. In this book, you will be able to read about the different subparts that compose the Internet of Things and the different ways to create a better IoT network or platform.
- This book will contain the possible architecture and middleware that you can use to create a platform and how to manage the data that you obtain from different objects (Smart Objects, sensors, or actuators) using a secure protocol or messages when you send the data through insecure protocols.
- These improvements can be applied in different ways. We can use different technologies and create different applications, or we can use the research of other fields like Big Data to process the massive data of the devices, Artificial Intelligence to create smarter objects or algorithms, Model-Driven Engineering to facilitate the use of any people, Cloud Computing to send the computation and the applications to the cloud, and Cloud Robotics to manage and interconnect the Robots between themselves and with other objects.
-This book will bring forth the details in a precise and concise form about all the right and relevant technologies and tools to simplify and streamline the concepts, processes, model development, and budget development for readers of respective backgrounds.
Healthcare may be considerably improved with the use of Artificial Intelligence and Machine Learning (ML) systems. These systems can help with earlier diagnosis of diseases, as well as more specific treatment plans. As Big Data, the Internet of Things with many more smart technologies grows more widespread; Deep Learning is becoming more popular. Due to the apparent rising complexity and volume of data in healthcare, Artificial Intelligence (AI) will be used more frequently. This work aims to develop a Deep Learning-based smart healthcare monitoring system. This system keeps track of patients' health, analyses numerous parameters, categorizes data, and organizes requirements. The algorithm using the Python program is developed and discussed to track the health of several patients with various illnesses. This method also aids in the categorization of data, organization of pharmacological requirements.
The book is an informative guide for data and computer scientists working to improve disease detection techniques in medical and life sciences research. It also serves as a reference for engineers working in the healthcare delivery sector.
PREFACE
CHAPTER 1 IOT BASED WEBSITE FOR IDENTIFICATION OF ACUTE LYMPHOBLASTIC LEUKEMIA USING DL
CHAPTER 2 AI AND IOT-BASED INTELLIGENT MANAGEMENT OF HEART RATE MONITORING SYSTEMS
CHAPTER 3 DEEP LEARNING APPLICATIONS FOR IOT IN HEALTHCARE USING EFFECTS OF MOBILE COMPUTING
CHAPTER 4 INNOVATIVE IOT-BASED WEARABLE SENSORS FOR THE PREDICTION&ANALYSIS OF DISEASES IN THE HEALTHCARE SECTOR
CHAPTER 5 CONSTRUCTION AND EVALUATION OF DEEP NEURAL NETWORK BASED PREDICTIVE CONTROLLER FOR DRUG PREPARATION
CHAPTER 6 MACHINE LEARNING BASED PREDICTIVE ANALYSIS AND ALGORITHM FOR ANALYSIS SEVERITY OF BREAST CANCER
CHAPTER 7 GLAUCOMA DETECTION USING RETINAL FUNDUS IMAGE BY EMPLOYING DEEP LEARNING ALGORITHM
CHAPTER 8 TEXTURE ANALYSIS-BASED FEATURES EXTRACTION & CLASSIFICATION OF LUNG CANCER USING MACHINE LEARNING
CHAPTER 9 IMPLEMENTATION OF THE DEEP LEARNING-BASED WEBSITE FOR PNEUMONIA DETECTION & CLASSIFICATION
CHAPTER 10 DESIGN AND DEVELOPMENT OF DEEP LEARNING MODEL FOR PREDICTING SKIN CANCER AND DEPLOYED USING A MOBILE APP
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CHAPTER 11 FEATURE EXTRACTION AND DIAGNOSIS OF DEMENTIA USING MAGNETIC RESONANCE IMAGING
CHAPTER 12 DEEP LEARNING-BASED REGULATION OF HEALTHCARE EFFICIENCY AND MEDICAL SERVICES
CHAPTER 13 AN EFFICIENT DESIGN AND COMPARISON OF MACHINE LEARNING MODEL FOR DIAGNOSIS OF CARDIOVASCULAR DISEASE.
CHAPTER 14 DEEP LEARNING BASED OBJECT DETECTION USING MASK R-CNN
CHAPTER 15 DESIGN AND COMPARISON OF DEEP LEARNING ARCHITECTURE FOR IMAGE-BASED DETECTION OF PLANT DISEASES
CHAPTER 16 DISCERNMENT OF PADDY CROP DISEASE BY EMPLOYING CNN AND TRANSFER LEARNING METHODS OF DEEP LEARNING
CHAPTER 17 DEPLOYING DEEP LEARNING MODEL ON THE Google CLOUD PLATFORM FOR DISEASE PREDICTION
CHAPTER 18 CLASSIFICATION AND DIAGNOSIS OF ALZHEIMER’S DISEASE USING MAGNETIC RESONANCE IMAGING