book

Reshaping Intelligent Business and Industry

by Surjeet Dalal, Neeraj Dahiya, Vivek Jaglan, Deepika Koundal, Dac-Nhuong Le

October 2024

Intermediate to advanced

640 pages

21h 28m

English

Wiley-Scrivener

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1.1 Introduction1.2 Artificial Intelligence Agents1.3 Artificial Intelligence Algorithms1.4 Applications of Artificial Intelligence1.5 ConclusionReferences
2.1 Introduction2.2 Video Analytics2.3 Object Detection and Object Tracking2.4 Industrial Application2.5 ConclusionReferences
3.1 Introduction3.2 Literature Review3.3 Requirement Specification3.4 Testing and Validation3.5 Result3.6 Conclusion and Future WorkReferences
4.1 Introduction4.2 Literature Review4.3 The Need for Exploring XAI4.4 Scope of Explanation4.5 Differences in Research Methodology4.6 ConclusionReferences
5.1 Introduction5.2 What Is Artificial Intelligence?5.3 The Law and Policy Relating to AI in India5.4 The Morality Debate: The Ethicality of AI in Law5.5 ConclusionReferences
6.1 Introduction6.2 Predictive Analytics6.3 Machine Learning6.4 Applications of Supervised and Unsupervised Learning6.5 ConclusionReferences
7.1 Introduction7.2 Related Work7.3 Research Methodology7.4 Model Description7.5 ConclusionReferences
8.1 Introduction8.2 Literature Review8.3 Benefits and Major Components of IoT8.4 IoT Implementation and Building Blocks8.5 IoT Architecture8.6 ConclusionReferences
9.1 Introduction9.2 Application of IoT9.3 IoT Devices9.4 ConclusionReferences
10.1 Introduction10.2 Related Work10.3 Overview of Internet of Things (IoT)10.4 Security Issues Addressed Using Diverse Technologies10.5 Open Challenges and Future Research Directions10.6 ConclusionReferences
11.1 Introduction11.2 Related Work11.3 Methodologies Proposed11.4 Software Elements11.5 Project Cost Estimation11.6 ConclusionReferences
12.1 Introduction12.2 Literature Review12.3 Proposed Wi-Fi Communication Module12.4 IR (Infrared) Remote and Arduino Nano12.5 ConclusionReferences
13.1 Introduction13.2 Related Work13.3 Traditional and New Architecture of IoT13.4 Design Principles and Decision Framework of IoT13.5 Applications and Challenges13.6 ConclusionReferences
14.1 Introduction14.2 Inclusions in IoT Network14.3 IoT Interoperability Protocols14.4 Interoperability Conceptual Framework Proposed14.5 ConclusionReferences
15.1 Introduction15.2 Architecture of IoT15.3 Attacks on IoT15.4 Some Possible Solutions to Avoid/Prevent Cyberattacks15.5 ConclusionsReferences
16.1 What Are Smart Cities?16.2 Internet of Things16.3 Introduction to Artificial Intelligence16.4 AIoT in Smart Cities16.5 ConclusionReferences
17.1 Introduction17.2 Overview of Smart Cities17.3 AIoT in Smart Cities17.4 Open Issues and Challenges17.5 ConclusionReferences
18.1 Introduction18.2 Research Methodology18.3 The Risks and Challenges of Convergence in the Making of Smart Cities18.4 Results and Findings18.5 Future Research Directions for the Convergence of Blockchain, AI and IoT18.6 ConclusionReferences
19.1 Introduction19.2 Literature Review19.3 Proposed Methodology19.4 Conclusion19.5 Challenges and Future WorkReferences
20.1 Introduction20.2 AIoT Applications in the Education Sector20.3 IoT Development Stages20.4 ConclusionReferences
21.1 Introduction21.2 Literature Review and Hypotheses21.3 Methodology21.4 Results and Discussion21.5 ConclusionReferences
22.1 Introduction22.2 Literature Review22.3 IoT in Healthcare22.4 Role of Artificial Intelligence in Healthcare22.5 Challenges of IoT in Healthcare22.6 ConclusionReferences
23.1 Introduction23.2 Background23.3 AIoT in Healthcare23.4 AIoT Challenges and Opportunities23.5 ConclusionReferences
24.1 Introduction24.2 Problem Identification24.3 Proposed Methodology24.4 Findings and Discussion24.5 ConclusionReferences
25.1 Introduction25.2 Security Matters for IoT in Healthcare25.3 Cholesterol Control Levels25.4 IoR Device for Cholesterol Test: CURO L725.5 Challenges, Limitations, and Future Scope25.6 ConclusionReferences
26.1 Introduction26.2 Using Deep Learning and AI for Surveillance26.3 Other Ways that Do Not Rely on Machine Learning Knowledge26.4 The Present Position of Learning Algorithms and Patient Monitoring26.5 Possible Uses for Machine Learning Surveillance26.6 Concerns and Future Objectives26.7 ConclusionsReferences
27.1 Introduction27.2 Artificial Intelligence and IoT in Agriculture27.3 Components of AI and IoT for Agriculture27.4 Application of IoT and AI in Agricultural Automation27.5 Challenges and Opportunities27.6 Conclusion and Future TrendsReferences
28.1 Agricultural Process28.2 The Use of Artificial Intelligence in Agricultural Applications28.3 Predictive Analytics and Precision Agriculture28.4 Agricultural Robotics (Agrobots)28.5 AI-Enabled System for Pest Control and Disease Diagnosis28.6 Adopting AI: A Challenge for Farmers28.7 ConclusionReferences
29.1 Introduction29.2 Smart Road Traffic Management System (SRTMS)29.3 Smart Traffic Information System (TIS)29.4 Smart Parking Management System29.5 Smart Pavement Management System29.6 ConclusionReferences
30.1 Introduction30.2 Technical Challenges in Self-Driving Cars30.3 Other Very Critical Areas30.4 Blind Spots in Autonomous Vehicles30.5 Potential Cyberattacks on Automated Vehicles30.6 ConclusionReferences
31.1 Introduction31.2 Review of SDR Receiver Architectures31.3 Integration of SDR and IoT31.4 Artificial Intelligence31.5 Proposed AI-Based Receiver Architecture31.6 AI Optimization31.7 Results and Discussion31.8 ConclusionReferences
32.1 Introduction32.2 AI, IoT, and Big Data Analytics32.3 AIoT-Based Data Analytics and Decision-Making32.4 Challenges32.5 Role of AIoT in the Context of COVID-1932.6 Future Direction and ConclusionReferences
33.1 Introduction33.2 Literature Review33.3 Research Methodology33.4 Discussion, Analysis, Limitation and Future Work33.5 ConclusionReferences
34.1 Introduction34.2 Related Work34.3 Smart Mask Disinfection System34.4 Results and Discussion34.5 ConclusionReferences

Content preview from Reshaping Intelligent Business and Industry

32Artificial Intelligence of Things (AIoT) for Intelligent Data Design

PARUL GANDHI, RAJ KUMAR

Department of Computer Applications, Manav Rachna International Institute of Research and Studies, Faridabad, Haryana, India

Email: gandhi2110@gmail.com

Abstract

Artificial intelligence of things (AIoT) is the next critical step for the internet of things (IoT) — altering the process of data analysis and action. The internet of things is critical for gathering relevant, intelligent data and sharing it so that it can be processed, analyzed, and turned into actionable information. The purpose of artificial intelligence (AI) in IoT is to expedite the process of making sense of all the data generated. It will create new opportunities for IoT applications, since data analysis from hundreds of endpoints will be highly efficient.

Edge or cloud, the combination of AI and IoT creates a powerful new tool for organizations worldwide. IoT operations, human-machine interactions, and data management and analytics are the goals of the invention, which is sometimes referred to as artificial intelligence of things (AIoT). The use of AI analytics can transform IoT data into meaningful information for better decision-making.

Since this new technology is undergoing a revolution, this chapter explains a variety of terminologies associated with it in great detail. A basic overview of IoT architecture, AI, and AIoT-based systems is provided in this chapter. In addition, some proposed systems with their ...