The rapid integration of AI into IoT systems has outpaced the ability to explain and audit automated decisions, resulting in a serious transparency gap. We address this challenge by proposing a blockchain-based framework to create immutable audit trails of AI-driven IoT decisions. In our approach, each AI inference comprising key inputs, model ID, and output is logged to a permissioned blockchain ledger, ensuring that every decision is traceable and auditable. IoT devices and edge gateways submit cryptographically signed decision records via smart contracts, resulting in an immutable, timestamped log that is tamper-resistant. This decentralized approach guarantees non-repudiation and data integrity while balancing transparency with privacy (e.g., hashing personal data on-chain) to meet data protection norms. Our design aligns with emerging regulations, such as the EU AI Act’s logging mandate and GDPR’s transparency requirements. We demonstrate the framework’s applicability in two domains: healthcare IoT (logging diagnostic AI alerts for accountability) and industrial IoT (tracking autonomous control actions), showing its generalizability to high-stakes environments. Our contributions include the following: (1) a novel architecture for AI decision provenance in IoT, (2) a blockchain-based design to securely record AI decision-making processes, and (3) a simulation informed performance assessment based on projected metrics (throughput, latency, and storage) to assess the approach’s feasibility. By providing a reliable immutable audit trail for AI in IoT, our framework enhances transparency and trust in autonomous systems and offers a much-needed mechanism for auditable AI under increasing regulatory scrutiny.
Growing applications of Internet of Medical Things (IoMT) devices have revolutionized the healthcare sector because of remote patient tracking, diagnosis, and data-supported decision-making. The kind of medical data collected from these devices, however, is very sensitive, which makes it very vulnerable to issues of security, privacy, and integrity. This paper suggests a way to keep IoMT data safe using the Algorand blockchain, XChaCha20-Poly1305 encryption, and different types of decentralized storage. Using the platform's fast, highly scalable, and highly secure architecture, Algorand blockchain framework makes sure that encrypted patient medical records are stored permanently and cannot be changed. To properly encrypt sensitive IoMT data before storing the data in DSNs including IPFS, Storj, and Filecoin, a modern stream cipher called 'XChaCha20-Poly1305' is used. Decentralized storage ensures data accessibility and distribution simultaneously, minimizing reliance on associated server points that are susceptible to single points of failure. Besides data secrecy, accuracy, and anti-intrusion attack breakout measures, this work explores the security measures implied by this architecture. Additionally, it assesses the efficacy of various decentralized storage options and highlights their benefits and drawbacks when it comes to storing large amounts of medical data. It can be concluded that the proposed framework is cost-effective and capable of expansion and implementation in the modern healthcare environment of IoMT data protection.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Advanced Steganography and Watermarking Techniques
Evidence plays a crucial role in judicial systems, and managing it securely and efficiently ensures justice. This paper introduces Decentralized Trust, a framework that combines blockchain technology, Non-Fungible Tokens (NFTs), and fog computing to address common issues like tampering, delays, and reliance on centralized systems. Traditional methods that depend on cloud computing often face high latency and slow processing, especially in remote areas. This research also builds upon the challenges identified in previous studies, such as tampering vulnerabilities, inefficiencies in evidence processing, and accessibility issues in underserved regions, providing a novel and comprehensive solution through Decentralized Trust. Fog computing handles tasks closer to where data is created, reducing delays and improving response times. Blockchain ensures that evidence records cannot be altered, while NFTs make each piece of evidence unique and tamper-proof. The framework is organized into layers: edge nodes at police stations capture evidence, fog nodes process the data and create NFTs, and cloud storage, supported by the Interplanetary File System (IPFS), provides secure long-term storage. Results demonstrate that the framework achieves average transaction delays of 24.5 seconds on low-performance devices (Node A) and 168.9 seconds on high-performance devices (Node B), with margins of error showing efficient scalability even under significant processing loads. The observed transaction delays are due to differences in system architecture and processing priorities. High-performance devices (Node B) have more complex validation processes, increased security checks, or resource contention, contributing to longer transaction times. By combining these technologies, Decentralized Trust offers a reliable, fast, and secure way to manage judicial evidence, building trust in the framework while addressing the needs of remote and underserved areas.
The rapid evolution of smart cities has led to transformative advancements through the integration of IoT devices, sensors, and data-driven systems, yet has simultaneously exposed critical vulnerabilities in cybersecurity, data integrity, and trust management. This research proposes a Decentralized Trust Framework that leverages blockchain technology, AI-driven threat detection, and a Lightweight Adaptive Proof-of-Stake (LA-PoS) consensus mechanism to address these challenges. The framework integrates three key layers: a Blockchain Layer for decentralized trust and immutability, a Cybersecurity Layer employing cryptographic standards and AI-based anomaly detection, and a Data Integrity Protocol Layer for real-time synchronization and tamper-proof data validation. Performance evaluations indicate the framework achieves a threefold increase in transaction throughput, a 30% reduction in latency, and enhanced energy efficiency compared to traditional blockchain systems. Security metrics highlight a 98.2% threat detection rate and a substantial reduction in false positives, while resource optimization nearly doubles IoT device battery life. The framework demonstrates applicability in critical smart city use cases, including smart traffic management, energy systems, and public safety, providing secure, scalable, and efficient solutions for urban infrastructures. Despite these advancements, challenges such as interoperability among heterogeneous systems, computational overhead for IoT devices, and policy adoption persist. Future research will focus on optimizing interoperability protocols, incorporating quantum-resistant cryptographic techniques, and extending the framework to emerging domains such as autonomous systems and smart healthcare. The proposed framework provides a robust foundation for building sustainable, resilient, and trustworthy urban ecosystems, bridging gaps in current smart city technologies.
Internet of Things (IoT) has also brought about rapid adoption of technologies in agriculture that provides real-time monitoring and management of crop production, water usage, and soil health. Nevertheless, IoT devices combined with blockchain-based smart contracts create severe energy consumption issues, particularly when the resource is limited. This paper will present a framework that is energy-efficient to implement smart contracts in the network of IoT devices in the agriculture industry. “The proposed solution allows minimizing the computational overhead, preserving data integrity, transparency, and security by improving consensus mechanisms and scheduling transactions. According to the experimental simulations, the framework reduces the energy use by up to 35 percent of that of the existing blockchain execution models, without affecting the operational reliability. The results offer practical lessons towards sustainable precision farming whereby technological innovation is balanced with the environment.
Mohammad Nasrinasrabadi, Maryam A. Hejazi, Ehsan Chaharmahali, Mousa Hussein
The integration of blockchain and the Internet of Things (IoT) within smart grids offers transformative potential for enhancing energy management, security, and operational efficiency. Smart grids rely on advanced digital technologies to enable bidirectional communication between energy producers and consumers, optimizing the integration of renewable energy sources and promoting demand-side management. Blockchain technology, with its decentralized and immutable nature, ensures secure and transparent energy transactions while fostering trust without the need for centralized authorities. Meanwhile, IoT facilitates real-time data collection and monitoring, enabling dynamic energy management and transactive energy systems. This review explores the synergies between blockchain and IoT in addressing critical challenges such as cybersecurity, data security, and network security. By leveraging mechanisms like smart contracts and consensus algorithms, these technologies enhance grid resilience and privacy, providing robust solutions to manage distributed energy resources and decentralized energy markets. The integration also supports peer-to-peer energy trading, improves scalability, and reduces reliance on intermediaries, aligning with sustainability goals by promoting renewable energy adoption. Despite significant advancements, challenges such as regulatory barriers, high computational costs, and scalability limitations persist. This paper emphasizes the need for innovative approaches to overcome these issues and highlights emerging trends such as hybrid blockchain models and AI-enabled solutions. By addressing these gaps, blockchain and IoT can redefine smart grid infrastructures, ensuring a secure, efficient, and sustainable energy future.
Revolutionizing distributed agile software testing, we propose BCTestingPlus, a groundbreaking blockchain-based platform. In the traditional distributed agile software testing lifecycle, software testing has suffered from a lack of trust, traceability, and security in communication and collaboration. Furthermore, developers’ failure to complete unit testing has been a significant bottleneck, causing delays and contributing to project failures. Introducing BCTestingPlus, a transformative blockchain-based architecture engineered to overcome these challenges. This framework integrates blockchain technology to establish an inherently transparent and secure environment for software testing. BCTestingPlus operates on a private Ethereum blockchain network, offering superior control and privacy. By implementing smart contracts on this network, BCTestingPlus ensures secure payment verification and efficient acceptance testing. Crucially, it aligns development and testing teams toward shared objectives and guarantees equitable compensation for their efforts. The experimental results and findings conclusively show that this innovative approach demonstrates that BCTestingPlus significantly enhances transparency, bolsters trust, streamlines coordination, accelerates testing, and secures communication channels for all parties involved in the distributed agile software testing lifecycle. It delivers robust security for both development and testing teams, ultimately transforming the efficiency and reliability of distributed agile software testing.
Sunil P. Chinte, Prof. S. A. Thakare, Aarti R. Jaiswal, Nikunj Hasmukhrai Raja · 5 authors
The rapid expansion of Internet of Things (IoT) ecosystems has resulted in an unprecedented surge in data generation, necessitating reliable, scalable, and secure storage mechanisms. Traditional centralized storage systems suffer from inherent limitations such as single points of failure, limited scalability, and vulnerability to cyberattacks, which compromise the confidentiality and availability of critical IoT data. This study introduces a blockchain- based decentralized storage framework aimed at addressing these critical issues. By leveraging the distributed and immutable characteristics of blockchain technology, the proposed system enhances data integrity, ensures transparency, and facilitates trustless data exchange among heterogeneous IoT devices. The methodology includes mathematical modeling of key performance parameters such as latency, throughput, storage efficiency, and consensus delay. Smart contracts are integrated to automate validation and enforce rules among interconnected devices, while redundancy mechanisms like replication and erasure coding improve storage reliability and efficiency. The framework’s effectiveness is evaluated using simulation tools including Hyperledger Caliper and Ethereum Testnets for blockchain behavior, and NS-3 and OMNeT++ for modeling dynamic IoT network environments. Experimental results reveal a 30% improvement in data retrieval time, 25% gain in storage efficiency, 40% enhancement in system resilience, and a 50% increase in transaction throughput over conventional approaches. These metrics highlight the suitability of the proposed model for real-world applications requiring scalable and secure IoT data management, such as healthcare monitoring, smart cities, and industrial automation. The model’s reproducibility and modularity make it a robust solution for future research and deployment. Overall, this work demonstrates that blockchain-integrated decentralized storage frameworks present a transformative step toward resilient and scalable IoT infrastructures.
Juan de Anda-Suárez, José Luis López-Ramírez, Daniel Jiménez-Mendoza, José Manuel Benitez-Quintero · 7 authors
Autonomous Vehicles (AV) have been extensively studied in both scientific and social contexts. Over the past two decades, there has been a significant rise in their real-world applications, including neural networks, Blockchain, Internet of Things, autonomous navigation, computer vision, automation processes, and various other areas. Hence, it is imperative to investigate the interplay between software, hardware, and individuals. To guarantee secure and unaffected interactions within autonomous vehicle devices and networks, decentralized Blockchain technology is proposed. This study presents the introduction of a framework we named “DEMU-NAV” for an ecosystem that includes Artificial Intelligence (AI), humans, and robots. The framework makes use of a decentralized Blockchain, Smart-Contract (SC), and Internet of things (IoT) network. Our framework was implemented using Ethereum and Python, enabling us to oversee Blockchain, Smart-Contracts, and the IoT for the facilitation of autonomous vehicle navigation.
Blockchain or Distributed Ledger Technology’s (DLT) disruptive architecture will revolutionise both economic activity and social structure. Institutional crypto economics is a new analytic framework for studying that evolutionary process in general, and bitcoin in particular, it presents us with a new method of organising the world, just like the Internet did. Bitcoin will have a similar effect on economy, money and finance. Developing countries face multiple problems such as lack of financial services and infrastructure (road, railways, telecommunication, and others). The disruptive architecture of Blockchain or Distributed Ledger Technology is well suited to benefit developing countries. This will be clearly visible in the implementation and application of Internet of Things (IoT) in emerging services. The nature of innovation in service-sector-based technology in developing countries differs, and the nature of IoT as a potentially disruptive emergent service product technology enabler emphasises this difference. The conventional productprocess innovation divide may no longer be applicable: the true value in IoT rests in neither. It is present in the system as well as the data collected by all devices everywhere in the world. The services income, which is generated by a combination of intelligent apps, analytics, and system integration services, represents a considerably greater revenue possibility for both developers and consumers of IoT enabled use cases. This paper presents how a peer-to-peer network that provides coverage for low-power IoT devices bringing a new viewpoint to the cellular telecommunications market. The network is a decentralised IoT infrastructure that is built on a Blockchain or Directed Acyclic Graph (DAG) by the people, communities, and individuals to offer hotspots wireless to the communities that help creates opportunities in financial freedom, helps supply chains traceability, forestry control and others. The paper demonstrates that decentralised IoT networks based on Tangle DAG can reduce infrastructure costs by 35-40% while increasing wireless coverage by 60%, with 1.5 million devices per 100 hotspots. It makes a unique and significant contribution to the deployment of IoT on Blockchain or Distributed Ledger Technology, as well as its potential to reduce poverty by improving the effectiveness and efficacy of existing procedures in various sectors of developing countries.
H. Mohammed Ali, William J. Buchanan, Jawad Ahmad, Mwrwan Abubakar · 6 authors
We introduce TrustShare, a novel blockchain-based framework designed to enable secure, privacy-preserving, and trust-aware cyber threat intelligence (CTI) sharing across organizational boundaries. Leveraging Hyperledger Fabric, the architecture supports fine-grained access control and immutability through smart contract-enforced trust policies. The system combines Ciphertext-Policy Attribute-Based Encryption (CP-ABE) with temporal, spatial, and controlled revelation constraints to grant data owners precise control over shared intelligence. To ensure scalable decentralized storage, encrypted CTI is distributed via the IPFS, with blockchain-anchored references ensuring verifiability and traceability. Using STIX for structuring and TAXII for exchange, the framework complies with the GDPR requirements, embedding revocation and the right to be forgotten through certificate authorities. The experimental validation demonstrates that TrustShare achieves low-latency retrieval, efficient encryption performance, and robust scalability in containerized deployments. By unifying decentralized technologies with cryptographic enforcement and regulatory compliance, TrustShare sets a foundation for the next generation of sovereign and trustworthy threat intelligence collaboration.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Advanced Steganography and Watermarking Techniques
Rohan Menon, C.V.S Anirudh, K Pradeep, K. P. Vijayakumar
This paper presents a serverless blockchain transaction model built entirely on Amazon Web Services (AWS), combining AWS Managed Blockchain (Hyperledger Fabric) with AWS Lambda for smart-contract execution. By eliminating traditional server infrastructure, the proposed architecture reduces operational overhead, automatically scales with demand, and optimizes costs through pay-as-you-go billing. Integration with AWS Identity and Access Management (IAM) enforces fine-grained access control, while AWS CloudWatch delivers real-time monitoring and logging. Smart contracts run as stateless Lambda functions triggered by blockchain events, enabling a fully decoupled, event-driven workflow. Infrastructure provisioning is automated via AWS CloudFormation, and AWS Key Management Service (KMS) secures cryptographic keys. Comparative benchmarking shows significant improvements in scalability, fault tolerance, and total cost of ownership versus server-based deployments, making this model ideal for enterprise-grade distributed ledger applications.
Mohammad Sharif Uddin, Md. Alamgir Hossain, Tanvir Mahmud, Suman G. Das
The integration of blockchain with the Internet of Medical Things (IoMT) has emerged as a transformative approach in healthcare, offering enhanced security, privacy, and transparency in managing sensitive patient data. This paper explores the potential of blockchain technology in addressing critical challenges within IoMT-based healthcare systems, including data integrity, interoperability, and decentralization. By reviewing architectural frameworks, real-world applications, and scalability solutions, the study outlines how cryptographic methods, smart contracts, and decentralized storage mechanisms can optimize healthcare services. This highlights ongoing challenges such as standardization, storage demands, and performance trade-offs while proposing advanced cryptographic and architectural solutions. The findings provide a comprehensive roadmap for developing secure and scalable blockchain-integrated IoMT systems that can support real-time, privacy-preserving medical data management.
Karthika Veeramani, Suresh Jaganathan, Venkatavara Prasad D
Attendance systems that exist currently are time consuming and vulnerable to modification.The attendance system proposed here is efficient and immutable, using facial recognition for marking and blockchain technology (BT) to secure attendance data.Though facial recognition for marking attendance has overtaken other biometric methods for its convenience, the program to mark attendance is not free from modification by some third party.The novel idea of using permissioned blockchain technology as the solution helps create an immutable privately-owned ledger in a distributed manner for storing attendance data where the code to automate the process of the attendance system is also immutable.
In recent years, several research and development initiatives have focused on developing secure and trustworthy systems for the healthcare industry via pervasive and mobile healthcare (mHealth) solutions. State-of-the-art mHealth solutions primarily rely on centralized storage, such as cloud computing servers, which may escalate the maintenance costs, require ever-increasing storage infrastructure, and pose privacy and security risks to the health-critical data produced, consumed, and transmitted over ad hoc networks. To overcome these limitations, we conducted this study intending to synergize mobile computing (devices to process health-critical data) and blockchain technology (infrastructure to secure storage and retrieval of health-critical data), specifically addressing data security and privacy using a blockchain mHealth system. The research employs an incremental method by (i) developing a framework that acts as a blueprint to architect blockchain-enabled mHealth systems, (ii) implementing a suite of algorithms as a proof-of-concept to automate the framework, and (iii) experimental evaluations to validate the scalability, computation, and energy efficiency of the proposed solution. The proposed framework has been implemented as a frontend using a mobile application interface that exploits the backend via the InterPlanetary File System (IPFS) system and Ethereum blockchain for secure management of mHealth data. We use a case-study-based approach demonstrating how health units, medics, and patients can securely access and distribute health-critical data. For evaluation, we deployed a smart contract prototype on the Ethereum TESTNET network in a Windows environment to test the proposed framework. Results of the evaluation indicate (a) scalability with query response time (range: 10–41 ms), (b) computational performance (CPU utilization: 1.5% – 2.5%), and (c) energy efficiency (gas consumption: 40000 units for 1000 bytes). The proposed solution – framework, algorithms, and experimental evaluation – aims to advance state-of-the-art architecting and implementing cybersecurity mHealth solutions using blockchain technology.
Shereen Ismail, Raouf Mehannaoui, Eden Teshome Hunde, Hassan Reza
IoT devices are typically resource-constrained, with limited computational power, storage, and energy. Holochain, an emerging distributed ledger technology (DLT), offers the benefits of blockchain while overcoming its limitations, such as the reliance on consensus algorithms and a globally synchronized ledger. As a result, Holochain has garnered attention in the research community as a promising solution for distributed IoT applications. This paper reviews various DLTs in IoT distributed networks, focusing on the motivation for utilizing Holochain in these environments. We explore its key applications, challenges, and research insights. We propose the HoloSec framework, a conceptual security framework for IoT distributed networks that leverages Holochain’s agent-centric architecture, advanced cryptography, and machine learning (ML). The paper also illustrates the setup and implementation of a Holochain-based IoT network for a healthcare scenario and compares the performance of Holochain with traditional blockchain solutions. Initial experimental results show that Holochain achieves a latency of around 50 ms for data publishing and 30 ms for retrieval, with a throughput of approximately 20 transactions per second (TPS) on a single node, significantly outperforming blockchain, which shows higher latency (200 ms publish, 100 ms retrieve) and lower throughput (10 TPS). Finally, we examine key challenges associated with Holochain and outline future research directions aimed at enhancing its interoperability, scalability, security, and regulatory compliance in IoT environments.
Prasanna Ramakrisnan, Mohd Farhan Shah Ahmad Rusli, Mike Soon Tai Gan Hou
Online learning platforms have reshaped higher education, with digital certificates becoming a key qualification method. However, these certificates are vulnerable to forgery and falsification. This chapter examines the use of blockchain frameworks to enhance the security and verification of digital certificates at Universiti Teknologi MARA (UiTM), Malaysia. Blockchain technology, with its secure and decentralized nature, utilizes a distributed ledger to prevent tampering and unauthorized changes. By employing cryptographic hashes and interconnected blocks, the framework ensures transparency and tamper resistance. This decentralized approach revolutionizes certificate issuance and verification, securely recording transactions across a network of computers and enhancing the integrity of the process. The proposed framework offers a reliable solution for stakeholders to verify certificate authenticity confidently. This blockchain framework aims to instill trust in the certification process, making digital certificates symbols of security and transparency in online education.
Ravi Kumar Munaganuri, Yamarthi Narasimha Rao, Sai Chandana Bolem
This research is anchored on the burning need for irrigation optimization and crop water use efficiency improvement, which remains a challenge in smart agriculture processes. Traditional irrigation methods normally lead to inefficiency, resulting in wasted water and non-maximum crops. These traditional ways normally lack attributes of real-time adaptability and secure data management—things that are very key to modernizing agricultural practices. In this work, artificial intelligence (AI), Internet of Things (IoT), and blockchain techniques will be integrated to design a comprehensive system for monitoring and predicting soil moisture levels. In the proposed model, long short-term memory (LSTM) networks are considered for soil moisture level prediction, taking into consideration past data, weather, and crop type. LSTM networks are chosen here for their high performance in timestamp series prediction tasks with an mean average error (MAE) of 0.02 m 3 /m 3 over a 7-day forecast horizon. For real-time monitoring, IoT sensors based on long range wide area network (LoRaWAN) technology are field-deployed for conducting long-range communications while consuming very limited energy to extend the sensor battery life over 5 years and bring down the data transmission latency below 5 s. It has an inbuilt permissioned blockchain framework—Hyperledger Fabric—which offers a secure and transparent system for data management and maintaining a record of soil moisture data, irrigation events, and metadata from sensors. This ensures the immutability and integrity of sets of data. Smart contracts automate irrigation upon reaching preconfigured soil moisture thresholds, and hence zero data integrity breaches occur with a transaction throughput of 1,000 transactions per second, taken into view with smart contract execution latency of less than 2 s. Moreover, it utilizes reinforcement learning with Deep Q-Learning to derive an optimized irrigation schedule. In this regard, it enables learning optimal irrigation policies and implements them to improve efficiency in the usage of water by 25% and increases crop yield by 15% compared to the traditional methods. Clearly from field trials, results indicate evident efficiency of the integrated system: a 20% water usage reduction and a 12% increase in crop yield within one growing season. This is rather an innovative take on irrigation practices, increasing a great deal of accuracy and sustainability for such and providing a really strong solution toward better agricultural productivity and resource management.
Unmanned aerial vehicles (UAVs) have recognized as a pivotal technology for advancing wireless augmented reality (AR) applications. However, the considerable energy requirements during the rendering process present a formidable challenge, demanding a precise balance between energy efficiency and latency. Additionally, UAV-enabled systems may face significant security risks in untrusted environments. To solve these issues, we present a secure optimization framework for AR applications, where the blockchain is integrated into the system to provide distributed management and control functions. The critical information during the AR rendering process can be recorded in blockchain promptly to enhance security and privacy. In the proposed framework, a joint optimization problem is formulated to achieve the optimal trade-off between energy consumption and content delivery latency, where the rendering decision, resource allocation, and UAV placement are jointly optimized. Due to the tight coupling variables, the optimization problem is non-convex and difficult to be tackled by adopting the traditional method. To this end, we decouple the formulated problem and design a block coordinate descent (BCD)-based optimization algorithm. In the proposed algorithm, we innovatively combine the Lagrangian multiplier iterative (LMI) method and the deep reinforcement learning (DRL) approach to enhance the solving efficiency by implanting the LMI method into the learning environment of DRL. Simulation results demonstrate that the proposed method can perform well for AR applications compared to other baseline solutions and traditional DRL approaches.
Blockchain is becoming one of the fundamental technologies for the IoT, as it is a distributed ledger technology (DLT), and the environment provides secure and trustworthy mechanisms for distributed data management. In this paper, we propose an intelligent framework integrating blockchain technology, IoMT, and AI to monitor resource utilization, analyze the system's behavior, and optimize the utilization of the resources-an investigational setup. We simulated an IoT environment in which devices generate memory usage data sent on the network, thanks to the MQTT protocol, and then saved securely in a blockchain. Following this, automatic pattern analysis is adopted to identify the market demand and distribute the resources to the individual blocks in a way that will make each perform to the maximum. The structure we designed is such that the proposed system could expand and be compatible with many other IoT deployments, bringing about a new, innovative way of handling distributed data where confidentiality and security are most important. An experimental evaluation we conducted using simulations under controlled situations shows that the system can lower the latency and ensure a higher overall system reliability while at the same time preventing tampering and supporting the verification of data. The study's findings illustrate that Blockchain-based IoT systems are one of the technologies that can revolutionize several urban living areas, including but not limited to smart cities, industrial automation, and healthcare monitoring. Further works will focus on expanding this approach to its application in the real world, where problems like network scalability, consensus mechanism overhead, and the energy efficiency of the IoT devices are to be considered.