Название: Transforming Management with AI, Big-Data, and IoT
Автор: Fadi Al-Turjman, Satya Prakash Yadav
Издательство: Springer
Год: 2022
Страниц: 315
Язык: английский
Формат: pdf (true), epub
Размер: 41.1 MB

This book discusses the effect that Artificial Intelligence (AI) and Internet of Things (IoT) have on industry. Artificial intelligence (AI), the Internet of Things (IoT), and cloud computing are buzzwords in the modern technological era. AI is the technology that aims at making computers or machines equivalent to the human brain and thus capable of learning and problem-solving. AI-based applications can be integrated easily with other emerging technologies like IoT, cloud, Big Data, and Blockchain. IoT states a system of interrelated, connected objects or things that can collect and transfer data via the Internet. A substantial number of physical things are being associated with the Internet at an exceptional rate recognizing the concept of the IoT.

These IoT applications generate massive data, and cloud computing delivers a way for those generated data to travel to their endpoint. The adoption of cloud computing is recognized as a data-processing and storage facility. All real-time applications connected with IoT need just-in-time processing and quick action over the clouds. Implementation of these applications requires data storage and computational capacity generally provided by cloud-based services. AI techniques are used to process the stored data in a high-precision and just-in-time manner. The cloud is a powerful tool for transmitting data through the traditional Internet channels as well as via a devoted direct link. IoT becomes the source of generating huge data, and the clouds become crucial for data storage. Hence, the IoT and clouds are closely integrated to offer commercial business services and generally referred to as cloud-based IoT. Businesses like Amazon Web Services (AWS), Google, and Microsoft have become certain cloud-based IoT services leaders, making the challenge even more worthwhile. Further, cloud-based IoT is used to connect a wide range of smart things in various applications.

Various Big Data technologies include:

-(i) Column-based database: Traditional, queue-based databases are great for online trade processing at high modernized speeds, but as data volumes increase, they decrease in query performance, and data becomes more unorganized. Column-based databases stock data with a target on columns rather than rows, which allows for massive data squeezing and much faster inquiry times. The drawback of these databases is that they only permit batch updates with a much more delayed update time than traditional standards.

- (ii) Schema-less database or NoSQL database: Several database types suit into this category, namely, the Value Store and Document Store, which focus on the depository and recovery of massive volumes of partly organized, or organized data. In NoSQL, this refers only to SQL, which covers a range of contrasting database technologies. The NoSQL database fields for processing relational ancestors, active, semi-structured data with minimal dormancy make them well suited to the Big Data ecosystem. NoSQL is generally described as operational and analytical. NoSQL is a custom function criterion for enhanced auxiliary functions based on an incomplete standard, where data can be processed at unrealistic times. Other big names in the NoSQL field are Cassandra, Oracle NoSQL and MongoDB.

- (iii) Mass Parallel Processing (MPP) technologies process large volumes of data in parallel. A number of processors, each with their control system and memory, work in contrasting parts of the identical program. MPP is a static process that requires a static database function between all the processors involved.

- (iv) High-Performance Computing Cluster (HPCC) is a free source platform utilized for computing and rendering services to deal with Big Data workflows. The HPCC data design is determined by the customer end in line with the specifications. The HPCC system is projected and then planned to handle the most perplexing and data-intensive analytics-associated difficulties. The HPCC system is the only platform for a particular programming language for single architecture and data simulation. The HPCC system is planned to analyse large volumes of data to solve the perplexing problem of Big Data. The HPCC system is based on an organization control language with the Declarative and Procedural Nature of programming language.

- (v) Hadoop is a free source software structure that processes massive amounts of data and processes large amounts of data. Hadoop presents the tools needed to develop and run applications. The data is divided into blocks and stored on multiple connected nodes that work together; this set-up is suggested as cluster.

Contents:
Artificial Intelligence for Smart Data Storage in Cloud-Based IoT
Big Data Analytics and Big Data Processing for IOT-Based Sensing Devices
Untangling E-Voting Platform for Secure and Enhanced Voting Using Blockchain Technology
Role of Artificial Intelligence in Agriculture: A Comparative Study
Big dаta: Related Technologies and Applications
Digital Marketing: Transforming the Management Practices
Real-Time Parking Space Detection and Management with Artificial Intelligence and Deep Learning System
Credit Card Fraud Detection Techniques Under IoT Environment: A Survey
Trustworthy Machine Learning for Cloud-Based Internet of Things (IoT)
A Novel αβEvolving Agent Architecture for Designing and Development of Agent-Based Software
Software-Defined Network (SDN) for Cloud-Based Internet of Things
Malware Discernment Using Machine Learning
Automating Index Estimation for Efficient Options Trading Using Artificial Intelligence
Artificial Intelligence, Big Data Analytics and Big Data Processing for IoT-Based Sensing Data
Technological Developments in Internet of Things Using Deep Learning
Machine Learning Models for Sentiment Analysis of Tweets: Comparisons and Evaluations
Secure and Enhanced Crowdfunding Solution Using Blockchain Technology