Industry 4.0 Convergence with AI, IoT, Big Data and Cloud Computing: Fundamentals, Challenges and Applications -  - E-Book

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Beschreibung

This volume showcases upcoming trends and applications that are set to redefine our technological landscape. Chapters comprise referenced reviews focused on the recent research that introduces new methods and techniques for using AI in Industry 4.0, and the integration of Internet of Things (IoT) to drive new industrial processes. The contributors have discussed challenges in industry 4.0 along with the applications and the way it is shaping different industries.

Key themes:
AI in Communication Media: Uncover the latest research, with insights into the challenges and adoption of AI in remote processes.
New AI Techniques for Industry 4.0: Learn about technologies such as blockchains and applications of machine learning, deep learning, and image processing.
IoT and AI for Smart Systems: Understand IoT with a special focus on enhancing smart systems, in different industries, including agriculture and transaction processing
Explorable AI: Gain a quick understanding of Explainable AI (XAI) and its role in improving the predictability and transparency of IoT applications.

Whether you're a tech enthusiast, researcher, or industry professional, this book offers a glimpse into the innovative world of Industry 4.0 and its intersection with AI, IoT, big data, and cloud computing.

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Seitenzahl: 295

Veröffentlichungsjahr: 2001

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Table of Contents
BENTHAM SCIENCE PUBLISHERS LTD.
End User License Agreement (for non-institutional, personal use)
Usage Rules:
Disclaimer:
Limitation of Liability:
General:
FOREWORD
PREFACE
List of Contributors
A Comprehensive Study of State-of-the-Art Applications and Challenges in IoT, and Blockchain Technologies for Industry 4.0
Abstract
1. Introduction
2. Integrated Blockchain-IoT Applications
2.1. Smart IoT-Healthcare
2.2. Smart Home
2.3. Smart Education
2.4. Drug Traceability
2.5. Power Grid
2.6. Smart Transportation System
2.7. Commercial World
2.8. Supply Chain
2.9. Automotive Industry
2.10. E-government
3. Challenges in the Adoption of Blockchain in IoT Environments for Industry 4.0.
3.1. Consensus
3.2. Storage Capacity and Scalability
3.3. Security
3.4. Smart Contracts
3.5. Legal Issues
3.6. Co-integration with IoT Platform
3.7. Virtual Ecosystem
3.8. Structurally Adaptable
3.9. Dynamic Expandability
3.10. Standardization
Conclusion
References
Role of Blockchain Technology in Industry 4.0
Abstract
1. Introduction of Industry 4.0
1.1. Core Value Drivers
1.2. The Nine Pillars of Industry 4.0
2. BLOCKCHAIN
2.1. Features of Blockchain
2.2. Evolution of Blockchain
2.2.1. Blockchain 1.0
2.2.2. Blockchain 2.0
2.2.3. Blockchain 3.0
2.3. Consensus Mechanism in Blockchain Technology
3. ROLE OF BLOCKCHAIN IN INDUSTRY 4.0
3.1. Healthcare
3.1.1. Issues in the Adaption of Blockchain in Healthcare
3.1.2. Current Application of Blockchain in Healthcare
3.2. Agriculture
3.2.1. Crop Insurance
3.2.2. Smart Agriculture
3.2.3. Food Supply Chain
3.3. Manufacturing
3.3.1. Commercial Impact of Blockchain
3.3.2. Automating Across Boundaries while Enabling Trust
3.3.3. Blockchain’s Case Studies in Manufacturing
3.3.4. Best Practices for Blockchain Solutions
3.4. Government
3.4.1. Building Trust in Government
3.4.2. Benefits of Solving the Problems Unique to Government with Blockchain
3.4.3. Case Studies
3.5. Education
3.5.1. Benefits for Students
3.5.2. Benefits for Institutions
3.5.3. Benefits for Employers
3.5.4. Using Blockchain for University Curricula
3.5.5. Blockchain’s Role in Lowering Education Costs
CONCLUSION
ACKNOWLEDGMENTS
REFERENCES
Adoption of Industry 4.0 in Remotely Located Industries
Abstract
1. INTRODUCTION
2. COMPONENTS OF INDUSTRY 4.0
2.1. Internet of Things (IoT)
2.2. Autonomous Robots
2.3. Big Data
2.4. Simulation
2.4.1. Benefits of Simulation Software
2.5. Cloud Computing
3. BENEFITS OF INDUSTRY 4.0
4. IMPLEMENTING INDUSTRY 4.0: CHALLENGES, ISSUES, AND SOLUTIONS
5. CASE STUDY: LEATHER MANUFACTURING UNIT
5.1. IoT-Based Area Measuring Machine
CONCLUSION
REFERENCES
Predictive Analytics Algorithm for Early Prevention of Brain Tumor Using Explainable Artificial Intelligence (XAI): A Systematic Review of the State-of-the-Art
Abstract
1. INTRODUCTION
1.1. Explainable AI
1.2. Some Key Concepts Related to XAI
1.3. Significance of Explainable Artificial Intelligence
1.4. LIME (Locally Interpretable Model Agnostic Explanations)
1.5. SHAP (SHapley Additive exPlanation)
2. MOTIVATION
3. RELATED WORKS
4. GAP ANALYSIS
5. PROPOSED METHODOLOGY
6. ALGORITHMS FOR THE PROPOSED SYSTEM
6.1. PSO (Particle Swarm Optimization)
6.2. SSO (Salp Swarm Optimization)
7. DESIGN ISSUES AND CHALLENGES
CONCLUSION AND FUTURE WORK
ACKNOWLEDGEMENT
References
Designing a Human-centered AI-based Cognitive Learning Model for Industry 4.0 Applications
Abstract
1. Introduction
2. National and International Status
3. Research Methodology
4. Results
Conclusion
References
Integrating Internet of Things (IoT), Machine Learning (ML), and the Cloud Infrastructure to Monitor Driving Behavior for Usage-based Insurance in the Indian Context
Abstract
1. INTRODUCTION
2. BACKGROUND
3. METHODOLOGY
3.1. Data Collection Environment
3.2. Random Forests Algorithm
3.3. Proposed Architecture
3.4. Proposed UBI Strategy
4. RESULTS AND DISCUSSION
CONCLUSION
REFERENCES
Academic Emotion Prediction in Online Learning Utilizing Deep Learning Approach
Abstract
1. INTRODUCTION
2. LITERATURE SURVEY
3. METHODOLOGY
3.1. Converting Image to Gray Scale
3.2. Detecting the Face in the Image Using OpenCV HAAR Cascade
3.3. Crop the Image of the Face and Resize it to 200 * 200
3.4. Save the Image
3.5. Adding Emotion Column in the Dataset
3.6. Training the Convolution Neural Network
4. RESULT AND DISCUSSION
CONCLUSION AND FUTURE WORK
REFERENCES
Implementation of Fruit Quality Management and Grading System using Image Processing and ARM7 Platform
Abstract
1. INTRODUCTION
2. Literature Review
3. Proposed System
3.1. ARM7 Processer LPC2148
3.2. IR Sensor
3.3. Web Camera
3.4. DC Motor
3.5. LCD Display
3.6. Load Cell
3.7. Signal Conditioning
3.8. Personal Computer
4. System Hardware and Software Specifications
5. System Flow Chart and Working of System
5.1. System Flow Chart
5.2. Working of System
6. Results and Discussion
Conclusion and future scope
Abbreviations
References
Internet of Things-based Smart Sensing Mechanism for Mining Applications
Abstract
1. Introduction
2. Literature Review
3. Smart Material
3.1. Methodology
3.2. Stages of Mining Life Cycle
3.3. The Mining Industry’s High-Level IIoT Architecture
4. Mining Applications
Conclusion And Future Work
References
Explainable Artificial Intelligence (XAI) for IoT
Abstract
1. INTRODUCTION
2. Motivation
3. Related Work
4. Research Gap
5. Issues and Challenges
6. Proposed Work
6.1. Overview of the Proposed Approach
Conclusions and Future Outlook
List of Abbreviations
References
Explainable AI (XAI) for Agriculture
Abstract
1. INTRODUCTION
2. NEED FOR AI IN AGRICULTURE
3. ROLE OF AI IN AGRICULTURE
3.1. Crop Yield Prediction
3.2. Intelligent Spraying
3.3. Crop and Soil Monitoring
3.4. Disease Diagnosis
3.5. Agriculture Robots
3.6. Predictive Insights
4. EXPLAINABLE AI IN AGRICULTURE
5. OVERVIEW OF EXPLAINABLE AI IN AGRICULTURE
6. PROPOSED WORK
7. FUTURE SCOPE AND LIMITATIONS
CONCLUSION
ACKNOWLEDGMENTS
REFERENCES
IoT and Big Data Analytics
(Volume 4)
Industry 4.0 Convergence with
AI, IoT, Big Data and Cloud Computing:
Fundamentals, Challenges and Applications
Edited by
Parikshit N. Mahalle
Vishwakarma Institute of Information Technology
Pune, Maharashtra, India
Gitanjali R. Shinde
Vishwakarma Institute of Information Technology
Pune, Maharashtra, India
&
Prachi M. Joshi
DES Pune University
Pune, Maharashtra, India

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FOREWORD

The boundaries between the physical and virtual worlds are becoming progressively blurred in what are known as cyber-physical production systems as a result of information and communications technology (ICT) being widely used by the manufacturing industry and traditional production operations (CPPSs). Intelligent machines are constantly exchanging data regarding current stock levels, issues, and modifications in orders or demand levels. In order to increase productivity and optimise throughput times, capacity utilisation, and quality in development, production, marketing, and purchasing, processes and deadlines are coordinated. Robotics, drones, nanotechnology, 3D printing, and artificial intelligence are just a few examples of the exponentially developing technologies that are accelerating and reshaping industrial processes.

The book outline and contents show that the major topic of the book is the brief introduction to the domain, research challenges, literature reviews and state-of-the-art, different algorithms/techniques/deployment methods. The book is divided into three sections that include challenges, convergence with AI and IoT Applications and Industry 4.0.

It starts with a comprehensive study of AI, IoT, Cloud Computing, and Blockchain Technologies. The Internet of Things (IoT), blockchain technology, and Artificial Intelligence (AI) are now acknowledged as advancements with the potential to change entire industries and enhance existing business processes. Blockchain, for instance, offers a shared and decentralized distributed ledger that can improve corporate operations' trust, transparency, security, and privacy. Similar to a register, a distributed ledger or blockchain can be used to hold any type of asset. For the German and European industries, automation of industries and user-friendliness of business processes are crucial. Finally, AI enhances business processes by identifying trends and maximizing their results. AI is structured based on a human mindset and an approach that is human-centered.

These key enablers for Industry 4.0 focusing on IoT, AI and Blockchain Technologies will help readers to empower their research and learning in these areas. Buyers, who belong to the category of researchers, will be benefited from the state-of-art and future research directions provided in the book. Practicing engineers will be benefited from the knowledge of the current challenges in technology, deployment methods and solutions. Postgraduate students will be introduced to new AI domains, and their related recent advancements. They will also be made aware of the rapid growth in the technology.

Pathan Mohd. Shafi Department of Computer Science and Engineering MIT ADT University, Loni Kalbhor Pune, Maharashtra, India

PREFACE

Artificial Intelligence (AI), the branch that has now captured the entire world with its power in dealing, predicting, and estimating with large amounts of data is on a roll. The need to apply intelligence, augment knowledge and enhance communication has made the AI domain more prevalent in emerging technologies. Moreover, the wide availability of varied types of media has made it desired to deliver and provide a robust communicating platform. The existence of potential approaches and techniques to deal with them has opened new avenues for researchers to combine AI methodologies to utilize the media and produce efficient outcomes in the process.

Further, the transformation and automation of traditional practices in industries – manufacturing and production have geared up in Industry 4.0. Integrating IoT, communication media and this digital transformation has become valuable as it has revolutionized the technology. The potential to transform with increasing demand to deliver smart solutions is opening broad perspectives for researchers and thus demanding more attention.

Working towards these new dimensions of AI - to deliver, communicate and process is gaining momentum. New solutions are being looked at to accommodate and improve the business domain. Detecting trends with analytics, interpreting the communicating data, and capturing futuristic estimates are the key factors required in today’s networking world. In recent years, researchers are gaining interest in this domain for various ubiquitous applications. To develop and deliver robust next-generation solutions with the applicability of Machine Learning, Deep learning and Data Sciences are used to overcome the challenges possessed by traditional approaches. This ranges from robotics to healthcare, and agriculture to sustainability.

This book focuses on the recent research that introduces new methods and techniques of AI for communicating media along with Industry 4.0.

Parikshit N. Mahalle Vishwakarma Institute of Information Technology Pune, Maharashtra, IndiaGitanjali R. Shinde Vishwakarma Institute of Information Technology Pune, Maharashtra, IndiaPrachi M. Joshi DES Pune University Pune, Maharashtra, India

List of Contributors

Avinash PatilMaharashtra Institute of Technology World Peace University, Pune, India Human Inspired AI Research Pvt. Ltd - HumInspAIRe, Pune, Maharashtra, IndiaEudes Smith M. LinheiroDepartment of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, Maharashtra, IndiaGitanjali R. ShindeVishwakarma Institute of Information Technology, Pune, Maharashtra, IndiaHriday Pandurang KhandagaleDepartment of Technology, Shivaji University, Vidyanagar, Kolhapur, IndiaJayashri BagadeDepartment of Information Technology, Bansilal Ramnath Agarwal Charitable Trust's, Vishwakarma Institute of Information Technology, Pune, IndiaMilind PandeMaharashtra Institute of Technology World Peace University, Pune, India Human Inspired AI Research Pvt. Ltd - HumInspAIRe, Pune, Maharashtra, IndiaMangesh BedekarMaharashtra Institute of Technology World Peace University, Pune, India Human Inspired AI Research Pvt. Ltd. - HumInspAIRe, Pune, Maharashtra, IndiaNeha MandoraHuman Inspired AI Research Pvt. Ltd. - HumInspAIRe, Pune, Maharashtra, IndiaNilesh P. SableDepartment of Information Technology, Bansilal Ramnath Agarwal Charitable Trust's, Vishwakarma Institute of Information Technology, Pune, IndiaPriyanka KuklaniHuman Inspired AI Research Pvt. Ltd. - HumInspAIRe, Pune, Maharashtra, India Northeastern University, Boston, Massachusetts, United StatesPriya ShelkeDepartment of Information Technology, Vishwakarma Institute of Information Technology, Pune, Maharashtra, IndiaPratap Pandurang HalkarnikarDr. D.Y. Patil Institute of Engineering, Management and Research, Nigdi Pradhikaran, Akurdi, Pune, IndiaPrasad Raghunath MutkuleVishwakarma Institute of Information Technology, Pune, Maharashtra, IndiaPrachi M. JoshiDES Pune University, Maharashtra, Pune, IndiaPawan S. WawageVishwakarma University, Pune, Maharashtra, IndiaPranali ChavhanDepartment of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, Maharashtra, IndiaPriyanka MoreDepartment of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, Maharashtra, IndiaParikshit N. MahalleVishwakarma Institute of Information Technology, Pune, Maharashtra, IndiaPrashant C. DhasVishwakarma Institute of Information Technology, Pune, Maharashtra, IndiaRiddhi MirajkarDepartment of Information Technology, Vishwakarma Institute of Information Technology, Pune, Maharashtra, IndiaRavesa AkhterNational Institute of Technology Srinagar, Srinagar, Jammu and Kashmir, IndiaRajesh PhursuleDepartment of Information Technology, Pimpri Chinchwad College of Engineering, Pune, IndiaSnehal RathiDepartment of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, Maharashtra, IndiaSaniya ZahoorNational Institute of Technology Srinagar, Srinagar, Jammu and Kashmir, IndiaVijay U. RathodDepartment of Artificial Intelligence and Data Science, G H Raisoni College of Engineering and Management, Wagholi, Pune, IndiaVarad VishwarupeAmazon Research and Development Centre, Bangalore, Karnataka, India Human Inspired AI Research Pvt. Ltd. - HumInspAIRe, Pune, Maharashtra, IndiaVijay P. BhatkarMaharashtra Institute of Technology World Peace University, Pune, IndiaVishal PawarMaharashtra Institute of Technology World Peace University, Pune, India Human Inspired AI Research Pvt. Ltd. - HumInspAIRe, Pune, Maharashtra, IndiaYogesh D. DeshpandeVishwakarma Institute of Information Technology, Pune, Maharashtra, India Vishwakarma University, Pune, Maharashtra, IndiaYuvraj V. ParkaleDepartment of Electronics and Telecommunication Engineering, SVPM’s College of Engineering, Malegaon (BK), Baramati, Maharashtra, India

A Comprehensive Study of State-of-the-Art Applications and Challenges in IoT, and Blockchain Technologies for Industry 4.0

Saniya Zahoor2,*,Ravesa Akhter2,Varad Vishwarupe1,4,Mangesh Bedekar3,4,Milind Pande3,4,Vijay P. Bhatkar3,Prachi M. Joshi5,Vishal Pawar3,4,Neha Mandora4,Priyanka Kuklani4,6
1 Amazon Research and Development Centre, Bangalore, Karnataka, India
2 National Institute of Technology Srinagar, Srinagar, Jammu and Kashmir, India
3 Maharashtra Institute of Technology World Peace University, Pune, India
4 Human Inspired AI Research Pvt. Ltd. - HumInspAIRe, Pune, Maharashtra, India
5 DES Pune University, Pune, Maharashtra, India
6 Northeastern University, Boston, Massachusetts, United States

Abstract

The Internet of Things (IoT) is a network of smart and self-configuring devices that exchange data by interacting with the environment to make decisions without human intervention. Endowed to sense surrounding events, these physical objects generate large amounts of real-time data that need an acceptable architecture with better security to process and convert it into meaningful information. Implementation of blockchain in IoT offers a secure, transparent and efficient mechanism to store and manage data generated by connected IoT devices. Even though the integration of blockchain with IoT is pretty recent, there are at present a huge number of applications that include smart healthcare, smart homes, e-government, automotive industry, smart education, precision agriculture etc. However, there are several challenges encountered in Blockchain-IoT integration which include anonymity, standardization, interoperability, heterogeneity, data privacy, smart contracts, legal issues, transparency, storage capacity and scalability, security, etc. This chapter presents the current state-of-the-art Blockchain-IoT integration in order to examine how blockchain could possibly improve the IoT ecosystem catered towards Industry 4.0. This chapter investigates the various application domains of Blockchain-IoT integration. It also discusses the main challenges faced in the adoption of blockchain in IoT environments for I4.0.

Keywords: Blockchain technology, Internet of things, Industry 4.0, Smart home, Smart education.
*Corresponding author Saniya Zahoor: National Institute of Technology Srinagar, Srinagar, Jammu and Kashmir, India; E-mail: [email protected]

1. Introduction

The rapid advancement of Internet of Things (IoT) technology has led to the increased use of a number of devices in a wide range of applications contributing to an extraordinary improvement in our day-to-day lives. IoT has led to an abrupt shift toward the digital world and has changed an ordinary world into a smart world. It has been estimated that there will be 20 to 50 billion IoT devices connected over the Internet by 2025. Therefore, the aim of IoT is to connect the entire world where objects sense the data about the surroundings and interact with each other making a digital representation of the real world. In an IoT system, a number of IoT devices, equipped with sensors and actuators, monitor surroundings and take necessary actions via intensive sensing and data aggregation over a network. The collected data from the IoT devices are transferred to fog or cloud via gateways (or edge) that perform pre-processing of data before transmitting over the network. IoT devices take the necessary action by executing commands using their actuators. The cloud gateway facilitates secure data transmission between the edge gateway and cloud servers. Cloud servers perform data processing such as data cleaning and structuring to store the required data in a particular context. Various data analytics techniques are used to find the insight into the data such as correlations and pattern findings, outlier detections, etc. Various machine learning models are used to create precise models for IoT control applications that send automatic alerts to actuators. The concept of blockchain came into existence in recent times because of its decentralized and peer-to-peer architecture. Blockchain finds its applicability in many fields such as healthcare, industry, supply chain management, etc. In most of these applications, there is a tremendous problem of trust due to a lack of the verification mechanism for sensitive information. Blockchain provides a mechanism where transactions are verified by a group of unreliable actors via a secure, distributed, transparent and audible ledger. Blockchain provides open and full access to all transactions occurred to date at any time. There are a number of protocols in blockchain for organizing the information in the form of blocks with each block storing the set of transactions performed at a given time. These blocks are linked together by a reference to the previous block, forming a chain of blocks. In blockchain systems, there are various services that should be provided by network peers to operate in the blockchain environment. The services include routing, storage, wallet, and mining. Fig. (1) shows the architecture for blockchain. Blockchain is considered an application software that is installed on several computers (nodes) in a network for registrations and transactions. In blockchain systems, a new block of information for each new register is created to the system. This new block is combined with the previous block of information using complex mathematical algorithms. The node which first calculates the new block transfers it to the other node on the network for approval. If approval comes, it is added as a new block in the blockchain system and accordingly updated on all nodes. Therefore, this creates a chain of blocks and is hence referred to as the blockchain.

Fig. (1)) Blockchain architecture.

Mining, storage, routing and wallet services should be provided by network peers to operate with the blockchain [4]. Different types of nodes can be part of the network as per the functions they provide. Table 1 summarizes some of the common node types in the Bitcoin network. Depending upon the level of security required and budget and nature of problem, we can have different types of nodes in a Bitcoin network based on the following characteristics.

Table 1Common node types in bitcoin network.CharacteristicsOpenSecludedHybridConsensus MechanismPricey Proof of work (Pow) requiredLight PowLight PowIdentity SecrecyMaliciousTrustedTrustedOwnership and SupervisionPublicCentralisedSemi-centralisedTime taken for TransactionMinutesMicrosecondsMicroseconds

In IoT environments, devices sense and produce a large amount of data which are transmitted over the Internet to other devices. Therefore, it requires the involvement of many participant devices for data sensing, transmission, aggregation, storage, processing, etc. Any data breach in these chains of participants can lead to fraud leading to huge economic losses to companies. Better control for secure data sharing between participants in these applications is required. The integration of blockchain with Internet of Things is a revolutionary step where information is shared between the participants in a secure manner. There has been recent research in the integration of blockchain with the Internet of Things and allied fields such as Wireless Sensor Networks (WSNs), cloud computing and fog computing. Blockchain provides a trusted information sharing service to the IoT environment, thereby enhancing the security of such systems. The other challenges addressed by integrated Blockchain-IoT environments include central point of failure, fault tolerance, scalability, authentication and authorization of IoT devices, reliability, etc.

A lot of work has been done in the field of Blockchain-IoT. In section 1.2 we have discussed the Blockchain IoT applications currently present in the literature and summarised the literature survey in Table 2.

Table 2Blockchain based security solution for few applications of IoT.S. No.ApplicationsIssues EncounteredSolution using BlockchainRemarks1.Smart IoT- HealthcareMalicious attacks [1], Resource constrained [2, 3], Incorrect prescription and wrong treatment [6], Information leakage [7], cyber accidents [8].Privacy preserving, data encryption, ethereum based smart contracts,Confidentiality, privacy, reduced single point failure, integrity, identity management, tamper resistance, immutability, QoS, Secure data sharing.2.Smart HomeRobbing, fire, carelessness towards elderly people.Home security controls, home monitoring, smart contract, Smart meter, CCTV.Security, privacy, homecare, automatic utility payment.3.Smart educationQuality of service issues (QoS) issues, Privacy leakage, Data integrity and repudiation issues.IoT-BC framework was implemented to communicate securely.Privacy, availability, integrity, confidentiality.4.Drug traceabilityQoS(Quality of service) issues, counterfeiting of drugsDrug ledger, Hyper ledger have been implemented for supply using blockchain to prevent forging,Supply chain management, enhance security, discernibility, traceability.5.Power gridUnreliability, energy wastage, unavailability of services.Extended Petra builds ledgers using blockchain to provide secrecy for communiqué, request and trading [25, 26].Smart metring, microgrid energy, energy trading.6.Smart transportation systemInconvenience faced in terms of traffic jam issues, parking issues.Smart devices, Collaborative info collecting by public blockchain [31]Enhances device security and privacy.7.Commercial worldQoS (Quality of service) issuesSmart agreement policy [32, 33], Media’s digital rights management system [34].Effective management of construction industries, user’s behaviour.8.Supply chainForging of items, mutability, lack of integrityRFID tags have been used in blockchain for agri-food supply management.Supply chain management throughout the process.9.Automotive IndustryForging of products like spare parts, lack of satisfaction and trust on brands,Supply chain management in whole automotive system.Supply chain management, reduced automotive system overheads.10.e-governmentInformation leakage, Cross-site scripting(XSS), structured query language (SQL) injection, Denial of service attacks (DoS), malware targeting [46]Secure information exchange technology for security.Confidentiality, integrity and availability.

2. Integrated Blockchain-IoT Applications

The integration of blockchain with the Internet of Things has paved the way to a multitude of applications in many sectors as discussed below.

2.1. Smart IoT-Healthcare

IoT in healthcare aids in real-time fitness monitoring and data access to bring about for patients’ well-being, enhanced healthcare procedures. In the medical field, the realm of IoT comprises justification, spontaneous info compilation, and perception. Since smart healthcare (IoT-enabled) systems deal typically with patients’ personal data and results, this data is tremendously under the influence of malicious attacks if not protected with innovative and formidable security methods [1]. Most of the smart healthcare devices like sensors, and actuators are resource-constrained. As a result, auxiliary security protocols cannot be incorporated in them [2, 3]. In addition, such devices are moveable and may need public network connections, such as in clinics, hospitals, cafeteria, homes, workplaces, etc., which further enhance to their exposure. Due to the exponential rise in connected IoT devices, designing vigorous and firm security mechanisms is a difficult task [4, 5]. For instance, the record of patients’ health condition is personal, and it necessities a security technique to prevent the information dispersion to an unofficial group. By working in this way, no one can perceive and influence the facts or get access to a patient’s health record. Besides this, it also averts a doctor from mistreatment of the patients. If no security practice is implemented, the physicians may give incorrect prescriptions or endow the wrong treatment to their patients [6]. For example, alterations to a blood investigation report might overstate a patient’s condition for transfusing mismatched blood in the course of the blood transfusion procedure. Severe cyber-attack alerts have happened in healthcare services in the past few years. In the year 2019, a high number of cases have been reported where HIPAA (Health Insurance Portability and Accountability Act) offense touched 418, and an about 34.9 million US nations had their protected health information (PHI) conceded in that year [7]. The prevailing infrastructure is not proficient to provide security contrary to such data breaches, which can eventually question the confidentiality and privacy of patients’ health information. The existing techniques in smart healthcare record another gap towards a challenging scenario, i.e., the presence of patients’ data in the guardianship of health administrations, leaving patients’ information at risk, and generating futile data distribution towards patients’ healthcare. For instance, just because the info of a patient’s well-being is not referred from one service provider to the other on time, the patient’s cure might get delayed. Electronic Health Record (HER) has such limits practically, which can be overwhelmed by using the blockchain technology. In recent times, it has been adopted by numerous government, private, and hybrid (both public and private) partnered projects [8]. In the field of healthcare, the benefits of blockchain technology were perceived when IBM Watson Health and the US Food and Drug Administration (FDA) dedicated a blockchain framework to guard data allied to oncology [9]. Blockchain obtains data from several sources and save it in the transaction audit log, which eventually aids in keeping track of the transparency and liability of data at the time of data interchange. It is supposed by the FDA (U.S. Food and Drug Administration) and IBM that blockchain has the ability to support data sharing collected from various sources with the consensus of patients and the terms equally agreed on [27]. Present working models are dependent on passwords, which may contain secret data (sensitive information) that have to be shared and are usually kept on untrustworthy and less protected clouds [4]. This resulted in several renowned cyber accidents. In the year 2014, the most well-known of which was the one, when hackers intruded into US Health insurer Anthem’s servers and the delicate info of about 80 million people (patients and employees) got stolen [8]. It is also of high significance that the healthcare data access must be handled with high precautions. Likewise, standardized checking is inevitable for ensuring data integrity. Blockchain decreases the threats of such calamitous breaches and ensures data privacy, integrity and robust storage. Moreover, single-point-of-failure is also lessened as this model stores data in a distributive computing way.

2.2. Smart Home

Smart homes using IoT lead to home automation. It is the mechanism that enables to control home appliances by electronically using internetworking systems. It includes setting up intricate heating, and lighting systems in advance, setting alarms, locking and unlocking the rooms, home security controls (watching homes), etc. all linked by a central system /hub and remote-controlled by end users.

Smart home info can easily be determined using blockchain technology as it is very easy to incorporate with heterogeneous IoT devices used in smart homes. Fig. (2) shows the blockchain-based ecosystem smart home using IoT. It is a conceptual framework of four layers consisting of the IoT layer, blockchain platform layer, application layer, and access layer [10].

Fig. (2)) Framework for blockchain based smart home ecosystem.

The IoT layer collects data from devices that are significant for measuring the state, environment, and inhabitants of smart homes. The requirements of IoT devices for smart homes are roughly characterized into three foremost categories; sensors, healthcare and multimedia. Environmental factors are measured using sensors. For instance, the thermostat sensor measures and regulates the temperature of a room. A closed-circuit television (CCTV), etc. is called a blockchain node. Facts from these nodes are merged and stored either in a centralized server or in a decentralized fashion like blockchain which makes the basic layer of the stack.

On top of the IoT ecosystem resides a blockchain technology. It comprises two main components: data structure, and a smart contract. Hash values are used to cryptographically link blocks. As a miner for authenticating and adding new relations to new blocks, a home server computer can be used. Smart contracts follow the rules which are predefined, and assist the decentralized relations. There are numerous ways to implement blockchain; private, public and hybrid, but generally in a smart home network, a private blockchain is preferred to reduce the overhead cost.

Application layer eases to use diverse smart home applications and their incorporation with prevailing blockchain platforms. It comprises smart home applications for instance homecare, data souk, management in accessing services, healthcare, automatic payment and smart city services. Most of these growing applications are adopting blockchain platform. Some are still under research.

Finally, at the topmost of the stack comes the Access layer. It allows stakeholders to value from smart home applications based on blockchain such as; microgrid, service providers, caregivers, retail shop, etc.

2.3. Smart Education

Education using the information and communication system (ICT) is known as the e-education system. Today’s whole education system is dependent on internet and its technologies. Mostly in the pandemic era of Covid-19, every task related to academics is performed using ICT. One of the prevalent accomplishments [11] was to build a framework for the education system to interconnect by means of blockchain and IoT technology on the Internet. This framework was mainly appropriate for the end users wherever the info is frequently taken to the linked devices on the internet. Besides that they have used a re-transmission policy, variable packet-length, to increase the system performance. Hence the implementation of IOT-BC dual framework is proposed [12]. The entire system has been realized as a three-tier architecture, fog, blockchain (BC), and Internet of Things (IoT). A token or symbol given by the accepted blockchain repository to the IoT device has the authority to link the model, get a notification key from the workstation, and gather info from the fog [13]. The IoT device can be a student, an employee or a tutor. IoT portable device determines the smart contacts from within the acceptable blockchain depository [14]. A primary server verifies the token or symbol from such an accepted blockchain repository or produces a key for each smart device as well as a reaction down to a device [15].

2.4. Drug Traceability

In medicine supply chain management blockchain plays a very important role in traceability and monitoring medicinal products while transportation. A lot of work has been done in this research area by incorporating IoT in blockchain. Huang Y et al. [17] used Drug ledger that has been designed to maintain the workflow of drug supply chain including packing, unpacking and repacking using blockchain technology. In [18, 19] blockchain technology has been used to track the counterfeiting of drugs by using encrypted QR for authentic manufacturers and Hyperledger using permissioned blockchain respectively. In a study [20], authors have clarified how to use Blockchain to enhance security, discernibility and traceability to the medicine supply chain. They were able to track the drugs from the producer to the end user.

2.5. Power Grid

Currently, everything is directly or indirectly dependent on the power grid. Maintenance of it is very tough. But using blockchain technology with IoT makes it very easy. Energy trading [21, 22], smart metering [23], and microgrid energy [24] are the power grid areas in which blockchain technology aids to offer a quick facility to consumers. A study [25, 26] clarified a strategy of blockchain-based transactive microgrid that can deliver transactional reliability through distributed computing nodes. The extension of PETra (builds on dispersed ledgers, such as Blockchains, and provides secrecy for communiqué, request, and trading) trading workflow have be used by them. In a study [27], a hybrid blockchain system has been used by combining public and private blockchain systems. It offers novel services to the power grid system.

2.6. Smart Transportation System

Transportation is the physical way by which one can connect to the rest of the world. Using Smart Transportation, it can be made more convenient and safe.

Smart Transportation system comprises seven [28] layers. Each layer consists of either some hardware devices or application oriented services that help in providing smart service. Once incorporating with blockchain technology, it improves the device security and privacy in both devices and data [29