The Bitcoin network comprises numerous nodes, necessitating users to invest significant network requests and time in comprehending its network topology. In this paper, we propose a Bitcoin network topology discovery algorithm that utilizes lightweight probe nodes to facilitate rapid transmission of network protocols. Building upon this, we introduce a node layer clustering algorithm based on filtering stable network nodes, enabling parallel discovery of the network topology. Additionally, we present an adaptive method for dynamically displaying the layered structure of the network topology. Experimental results demonstrate that our proposed method reduces communication overhead by approximately 72.16% when achieving a 95% similarity in network topology. Furthermore, the algorithm is applicable for discovering the network topology in other blockchain networks with similar structures.
The Metaverse is an evolving technology that leverages the Internet infrastructure and the massively connected Internet of Everything (IoE) to create an immersive virtual world. In the Metaverse, humans engage in activities similar to those in the real world, such as socializing, working, attending events, exploring virtual landscapes, creating and trading digital assets, participating in virtual economies, and experiencing entertainment and cultural activities. By using advanced technologies such as IoE, extended reality (XR), artificial intelligence (AI), machine learning (ML), and 6G communication, along with blockchain technology, the Metaverse bridges the physical and virtual worlds. In particular, Blockchain-Enabled IoE (BIoE) will play a crucial role in Metaverse applications by ensuring secure service provisioning through the integration of blockchain with IoE. It efficiently manages the massive connectivity of physical world objects and enhances security, integrity, and decentralization of trust, while increasing resilience against failures, thus securing and fostering trust in both physical and virtual Metaverse networks. While some view the Metaverse as a detached virtual world, technologies like mixed reality and digital twins highlight the need for complementarity and interactive co-existence between the physical and virtual worlds. Blockchain facilitates this co-existence by providing a secure and trusted framework for integrating and synchronizing data and activities across both environments, developing trust through the reliability and authenticity of interactions and transactions. However, despite substantial advancements in related fields, there remains a significant gap in comprehensive surveys that address the integration of AI/ML, 6G, and blockchain in the Metaverse. In this paper, we fill this gap by examining BIoE’s capabilities in bridging the physical and virtual worlds and securing Metaverse applications across various domains, such as immersive energy grids, immersive healthcare, and immersive living. We explore BIoE’s role in service provisioning in the Metaverse, including access control, privacy protection, authentication, attack identification, and trust management. Additionally, we present a detailed taxonomy of existing literature, discuss novel use cases, and explore the synergies and practical implementations of BIoE in Metaverse applications. Finally, we address current challenges and propose future research directions to advance the field of BIoE in the Metaverse.
Creating an immutable repository for vital robot and environmental data, ensuring long-term accessibility, and functioning in the absence of GPS or mapping are crucial for visual homing navigation systems. We focus on the intersection of blockchain and robotics, particularly in visual homing. Our research involves an in-depth analysis of various blockchain consensus mechanisms, highlighting their suitability for visual homing applications. The heart of blockchain functionality lies in its consensus mechanism, which facilitates agreement among network nodes. In our first study part, we conduct a comprehensive comparative analysis of key consensus algorithms, emphasizing visual homing’s decentralization, fault tolerance, latency, and throughput requirements. This analysis serves as a valuable reference for researchers and developers, emphasizing the importance of aligning the chosen consensus mechanism with specific blockchain application needs. The second part of our work involves extensive experiments exploring the connection between blockchain and visual homing. We assess prominent consensus mechanisms like Proof of Work (PoW), Proof of Stake (PoS), Delegated Proof of Stake (DPoS), and Proof of Authority (PoA) within a virtual environment in Gazebo, leveraging wide area visual navigation (WAVN). Our research implementation is grounded in the ROS framework and the Gazebo simulation environment.
Human Unreadable, İnsan bedenini gizleyen üç perdelik, bedensel, long-form (uzun biçimli) algoritmik bir koreografidir. Blok zincir üzerine kayıtlı bu çalışma dans, kriptografi, mühendislik, insan-makine etkileşimi, yapay zekâ, makine öğrenmesi ve plastik sanatlara ilişkin birçok disiplini sentezleyen bir yapıya sahiptir. Bu çalışmanın amacı, Operator ikilisi tarafıdan gerçekleştirilmiş Human Unreadable örneği üzerinden algoritmik sanatın, blok zincir teknolojisindeki yerini ve yeni varolma biçimini ortaya koymak ve web3 sanatının yaratıcılık potansiyellerini tartışmaktır. Bu örnekte, blok zinciri teknolojisi hem çalışmanın konusunun (beden ve gizlilik) bir parçasıdır hem de çalışmanın formunu oluşturan temel araçlardan biri ve elbette sunuş biçimidir. Sonuç olarak bu çalışmada olduğu gibi blok zincir üzerine kayıtlı bazı algoritmik sanat çalışmalarının bu teknolojiyi sadece satış, sergileme ya da arşivleme amacıyla değil aynı zamanda konunun ve formun bir parçası haline gelme yani blok zincir teknolojisini yaratıcı bir medyum olarak kullanma özelliği taşıdığını ifade etmek mümkündür. Çalışma ile ilgili elde edilen tüm bulgular literatür bağlamında yorumlanmıştır.
In metaverse, digital assets are essential to define identity, shape the virtual environment, and facilitate economic transactions. This study introduces a novel feature to the metaverse by capturing a fundamental aspect of individuals–their conversations–and transforming them into digital assets. It utilizes natural language processing and machine learning methods to extract a key sentence from user conversations and matches them with emojis that reflect their sentiments. The selected sentence, which encapsulates the essence of the user’s statements, is then transformed into digital art through a generative visual model. This digital artwork is transformed into a non-Fungible Token (NFT), becoming a valuable digital asset within the blockchain ecosystem that is ideal for integration into metaverse applications. Our aim is that the management of personality traits as digital assets will foster individual uniqueness, enrich user experiences, and facilitate more personalized services and interactions with both like-minded users and non-player characters, thereby enhancing the overall user journey.
Non-Fungible Tokens (or, for short, NFT) establish the ownership and the authenticity of digital assets. Regardless the high security levels provided by blockchain, are not excluded the cases where the ownership of a digital object may be claimed without proper rights. Fraud and copyright infringement should be prevented through the insurance of the authenticity and the integrity of a digital object associated with an NFT. In this work we consider the case of NFT images under the aspect of being susceptible to duplication, theft, tampering, fraud, or in general any potential threat against their authenticity and integrity properties. To deal with such cases we propose an integrated system that provides an a priori embedding of authenticity and integrity related information by deploying robust authenticity information hiding in the frequency domain alongside fragile integrity information hiding in the spatial domain before the image is being publicly available as NFT. Moreover, an automated secure procedure for the development of smart contracts alongside the development of an NFT dual that serves as backup and is not publicly available through the marketplace is proposed in order to retain the initial digital image. We design a modular architecture that incorporates all the components proposed in this work and discuss its potentials on its deployment over different digital objects that can be considered as NFTs.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Artists are digitally disenfranchised, rampant online sharing and ease of copying make protecting their work from unauthorized use an uphill battle. Digital art is effortlessly duplicated, shared, and manipulated without credit or compensation, even leading to individuals profiting off stolen work. This widespread issue, particularly plaguing social media, demands a solution. We propose a blockchain-based platform utilizing Non-Fungible Tokens (NFTs) to empower artists. By creating NFTs for their art, they claim irrefutable ownership, authenticity, and copyright, enabling secure sales via cryptocurrencies and combating unauthorized use. This innovative approach empowers artists to thrive in the digital age
Open access
Visual Attention and Saliency Detection
Generative Adversarial Networks and Image Synthesis
Gang Kou, Hasan Dınçer, Dragan Pamučar, Serhat Yüksel · 7 authors
Necessary improvements should be made to increase the effectiveness of non-fungible tokens on the Metaverse platform without having extra costs. For the purpose of handing this process more efficiently, there is a need to determine the most important factors for a more successful integration of non-fungible tokens into this platform. Accordingly, this study aims to determine the appropriate the identity management choices of non-fungible tokens in the Metaverse. There are three different stages in the proposed novel fuzzy decision-making model. The first stage includes prioritizing the expert choices with artificial intelligence-based decision-making methodology. Secondly, the criteria sets for managing non-fungible tokens are weighted by using Quantum picture fuzzy rough sets-based M-SWARA methodology. Finally, the identity management choices regarding non-fungible tokens in the Metaverse are ranked with Quantum picture fuzzy rough sets oriented VIKOR. The main contribution of this study is that artificial intelligence methodology is integrated to the fuzzy decision-making modelling to differentiate the experts. With the help of this situation, it can be possible to create clusters for the experts. Hence, the opinions of experts outside this group may be excluded from the scope. It has been determined that security must be ensured first to increase the use of non-fungible tokens on the Metaverse platform. Similarly, technological infrastructure must also be sufficient to achieve this objective. Moreover, biometrics for unique identification has the best ranking performance among the alternatives. Privacy with authentication plays also critical role for the effectiveness of this process.
Joaquín Cerdá Boluda, Marta C. Mora, Nuria Lloret, Stefano Scarani · 5 authors
The emergence of the Metaverse is raising important questions in the field of human-machine interaction that must be addressed for a successful implementation of the new paradigm. Therefore, the exploration and integration of both technology and human interaction within this new framework are needed. This paper describes an innovative and technically viable proposal for virtual shopping in the fashion field. Virtual hands directly scanned from the real world have been integrated, after a retopology process, in a virtual environment created for the Metaverse, and have been integrated with digital nails. Human interaction with the Metaverse has been carried out through the acquisition of the real posture of the user's hands using an infrared-based sensor and mapping it in its virtualized version, achieving natural identification. The technique has been successfully tested in an immersive shopping experience with the Meta Quest 2 headset as a pilot project, where a transactions mechanism based on the blockchain technology (non-fungible tokens, NFTs) has allowed for the development of a feasible solution for massive audiences. The consumers' reactions were extremely positive, with a total of 250 in-person participants and 120 remote accesses to the Metaverse. Very interesting technical guidelines are raised in this project, the resolution of which may be useful for future implementations.
Videos and image processing have significantly transformed computer vision, enabling computers to analyze, and manipulate visual data. The proliferation of cameras and IR equipment has facilitated the collection of valuable information about individuals and their surroundings. These technologies find applications in various domains, ranging from biometric entry cards and high-security clearances to surveillance. These applications form part of the Internet of Things (IoT), forming a centralized network. However, the proliferation of data and its sharing brings challenges related to security, privacy, and storage. Interactions with third-party systems may introduce vulnerabilities. To address these issues, researchers in computer vision have explored the integration of blockchain technology into various applications. This paper presents a comprehensive survey of blockchain applications in computer vision, focusing on image and video data sharing, video surveillance, biometrics, and video integrity protection. The aim is to explore how the blockchain can enhance the security, privacy, and authentication of them. It also discusses tools and techniques employed at the edge to achieve these objectives while highlighting opportunities for further improvements. Overall, this review provides insights into the integration of blockchain and computer vision, advancements, challenges, and future directions in leveraging image and video data in a blockchain-enabled environment.
Open access
Blockchain Technology Applications and Security
Visual Attention and Saliency Detection
Advanced Steganography and Watermarking Techniques
Kasun Moolika Gedara, Minh Nguyen, Weiqi Yan, Xue Jun Li
In this paper, we explore video blockchain for establishing connectivity among vehicles in a smart city through utilizing blockchain technology. By leveraging intelligent vehicular systems that provide location-based visualization through multiple deployed cameras in vehicles, we expand the scope of collecting video surveillance data for observation, thereby enhancing overall situational awareness. We utilize the decentralized nature of blockchain to implement a vehicle-based surveillance system across a smart city. To ensure reliability, the integration of two cryptographic functions, hashing and signing, with the blockchain is employed. This integration ensures secure and tamper-proof solutions for the existing intelligent surveillance system. In this paper, our primary focus is on combining blockchain technology to achieve sustainable and robust smart solutions for intelligent vehicular distributed video networks while eliminating the need for third-party intermediaries. Through extensive experiments and analysis, we demonstrate the effectiveness and feasibility of our proposed video blockchain approach. The results indicate that this innovative framework provides enhanced security, privacy, and scalability for intelligent vehicular distributed networks in smart cities, paving the way for a connected and efficient urban environment.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Technology has become a fundamental part of our environment, yet the borders between the physical and virtual realms become even more blurred. The introduction of the Metaverse is one of the most recent and notable innovations. It, just as any other technological advances, adapts to evolution in user needs serving as a link between the real and digital realms. While people can buy goods and services with a certain currency in the physical realm, cryptocurrencies and non-fungible tokens (NFTs) are used for transactions in the Metaverse. NFT provides customers a certificate of ownership, which means that their virtual commodities or assets such as lands or objects cannot be replicated. They may also be used to represent social standing, just like tangible goods and services. It has become increasingly common to come across museums displaying artworks or artists who sell their artworks as Non-fungible tokens (NFTs) on digital platforms such as Rarible, Mintable or OpenSea. This research discusses the 3D printability of NFTs and proposes a framework in order to create a hybrid experience for 3D printed NFT artworks. The results have shown that 3D printing of NFTs provided users/customers a hybrid experience in both realms, maintaining the artworks’ uniqueness and rarity, proof of ownership, as well as physical copies in hand. Moreover, the artists who were afraid of publicly displaying their artworks for the concern of being copied have created 3D printable designs that enabled them to easily and safely promote their designs to the public.
The current large blockchain systems (BTC Lightning network, Ethereum, etc.) are generally facing the problems of low persistence rates and high storage costs. Therefore, users tend to store single modal (textual) information on the existing blockchain systems. Inspired by semantic communication algorithms, this paper presents a new algorithm to solve the serious imbalance between textual and visual modals on blockchains. After semantic sampling of the original visual image, the resulting semantic text will be stored on the chain, and the end users can reconstruct a semantically similar image using the \textbf{R}elative \textbf{O}ptimal \textbf{S}emantic \textbf{I}sotope \textbf{S}election algorithm. Experiments on the DIV2K dataset show that the blockchain with our algorithm can achieve 430,000 times the storage capacity and 550,000 times the persistence rate for the original visual data with acceptable semantic information loss.
Abstract The indiscriminate distribution of a large number of unlicensed images through the Internet seriously harms the benefits of image owners, which prompts the study of image copyright protection solutions. Existing blockchain‐free solutions are limited to using centralized servers to store copyright information, leaving data vulnerable to being lost or tampered with by external attacks. Although the blockchain‐based image copyright protection solutions are capable of addressing the above problem, improvements are needed in choosing a suitable blockchain platform and supporting integrated copyright life cycle management. To this end, this paper designs a blockchain‐based reliable image copyright protection system named BB‐RICP using Hyperledger Fabric. For one thing, the adoption of Fabric mitigates the limitations of other blockchain platforms represented by Ethereum in terms of efficiency, economy, and availability. For another, BB‐RICP successes in achieving integrated copyright lifecycle management. In addition, BB‐RICP achieves enhanced applicability performance by firstly introducing GM algorithms recommended by Chinese national standard and adapting the more consortium blockchain‐oriented practical byzantine fault tolerance algorithm. Moreover, the adoption of spread spectrum watermarking brings convenience to users. Finally, Kubernetes is used to assist in the simulation of BB‐RICP to verify that users can operate reliably in the blockchain network.
Open access
2 source records
Advanced Steganography and Watermarking Techniques
Zuobin Ying, Wusong Lan, Chen Deng, Lu Liu · 5 authors
The metaverse provides us with an attractive virtual space in which the value of the virtual property has been increasingly recognized. However, the lack of effective cross-metaverse trading tools and the reputation guarantee makes it difficult to trade items among different metaverses. To this end, a decentralized reputation system for virtual items trading forum named DVIT is devised. To the best of our knowledge, DVIT is the first decentralized cross-metaverse item trading prototype inspired by the online-game trading system. We designed the corresponding transaction function and realized the autonomous governance of the community by introducing the reputation mechanism. An improved election mechanism is proposed to improve efficiency based on Delegated Proof-of-Stake (DPoS). Through token rewards associated with activity levels, users’ motivation can be stimulated. The experiments indicate that our proposed scheme could dynamically measure the trustworthiness degree of the users through the dynamic reputation value and thereby exclude malicious users from the blockchain within 20 epochs.
Amaç: Global ticari markalar son yıllarda metaverse ile ilgili hedef kitleleri ile etkileşime girmek, marka imajını kuvvetlendirmek için çeşitli projelere imza atmaktadırlar. Bu makalenin amacı biri orta segmentte hızlı, ikincisi ise lüks segmentte moda markası olan 2 giyim markasının metaverse alanına giriş yaparak yönettikleri projelerin marka imajlarına ve takipçileri ile olan etkileşimlerine katkı sağlayıp sağlamadıklarının incelenmesi ve analizlerini içermektedir. Gereç ve Yöntem: Zaman içerisinde sınırlandırılmış birkaç durumu çoklu kaynakları içeren veri toplama araçları ile derinlemesine incelendiği, durumların ve duruma bağlı temaların tanımlandığı nitel bir araştırma yaklaşımı olarak özgün vaka incelemesi yöntemi ile değerlendirilerek açıklayıcı format kullanılmıştır. Bulgular: Metaverse için gerekli altyapıyı destekleyecek enerji kaynakları ve ekipman ürünlerinin yönetimi gibi sorunların aşılması gerekmektedir. Meta veri tabanının bileşenleri olan AR/VR teknolojileri, çevrimiçi çok oyunculu oyunlar, dijital sanal ikizler ve blok zincir uygulamaları bir süredir aktif olarak kullanılmaktadır. Ayrıca son dönemde oldukça popüler olan Non Fungible Token (NFT) tabanlı olan sanat eserlerinin, hediyelik eşyaların ve arazilerin alınıp satılmasına olanak sağlayan teknolojik gelişmeler, vaat edilen evrenin bir adım daha yakın olduğunu gösteriyor. Ancak bu kurgusal evrenin tam anlamıyla gerçekleşebilmesi için 5G teknolojisinin devreye girmesi, AR/VR donanım ve içeriğinin yaygınlaşması, peer2peer teknolojilerinin kullanımının artması gerekmektedir. Metaverse tasarlandığı gibi hayata geçirildiğinde, dijital bir evrende 3D avatar oluşturarak çalışmak, seyahat etmek, alışveriş yapmak, okula gitmek, eğlenmek gibi birçok günlük aktiviteyi gerçekleştirmek mümkün olacaktır. Kullanıcıların meta veri deposunda yaptığı herhangi bir değişiklik, neredeyse herkes tarafından kalıcı olarak görülebilecek ve böylece kullanıcılara daha fazla kimlik ve deneyim sürekliliği sağlanacaktır. Bu değişimlerin sosyo-kültürel ve psikolojik etkileri de incelenecek bir konu olacaktır. Sonuç: Metaverse şu an başlangıç aşamasında olup bu platformda istikrarlı ve belli bir stratejiye dayalı projeler üreten çok az marka vardır. Bunların çoğu da popüler olan global markalardır. Metaverse evreninin daha büyük kitleleri kendisine çekme yönünde gelişmesi için bu büyük global markaların yanı sıra lokal markaların da çok katman oluşturacak şekilde var olması gerekiyor ki bu evren daha hızlı bir şekilde gelişsin.
The immense success of Bitcoin has also highlighted the hidden potential of blockchains and distributed ledgers in general. However, most blockchains are based on the so-called Proof-of-Work principle, which requires significant resources, making them unsuitable for the growing number of Internet of Things devices, not to mention other problems such as ensuring privacy and resistance to quantum computing. This paper, therefore, analyses current approaches in the field of ledgers with applications for the Internet of Things. Based on this, it presents a new ledger architecture for cultural heritage preservation that is energy sustainable and tailored to smartphones while pushing the deployment boundaries closer to the rest of the Internet of Things world. It is also resistant to quantum computing and provides privacy with accountability. Moreover, the developed solution considers not only the core technological structure but also its broader social (business) context, i.e., links to the tourism sector. This is performed by incorporating the relevant business model, as business models are important for the successful adoption of new technologies.
Trustworthy and real-time video surveillance aims to analyze the live camera streams in a privacy-preserving manner for the decision-making of various advanced services, such as pedestrian reidentification and traffic monitoring. In recent years, edge computing has been identified as a promising technology for trustworthy and real-time video surveillance because it keeps confidential video data locally and reduces the latency caused by massive data transmission. Generally, a single edge device can hardly afford the computation-intensive video analytics tasks. Most existing solutions incorporate cloud servers to handle the overloaded tasks. However, such an edge-cloud collaboration approach still suffers from unpredictable latency and privacy concerns because the remote cloud is centralized and distant from the cameras. In this work, we designed a blockchain-based collaborative edge intelligence (BCEI) approach for trustworthy and real-time video surveillance. In BCEI, geo-distributed edge devices form a peer-to-peer network to maintain a permissioned blockchain and share data and computation resources to perform computation-intensive video analytics tasks. The video analytics results are written on the blockchain in an immutable manner to guarantee trustworthiness. To reduce task execution time, we formulate and solve a joint stream mapping and task scheduling problem to schedule video streams and machine learning models among edge devices. A pedestrian reidentification prototype is implemented and deployed based on BCEI with the extensive performance evaluation, indicating the superiority of BCEI in latency reduction and system throughput improvement by leveraging collaboration among edge devices.
As the core of blockchain technology, the consensus algorithm directly affects the security, stability, and decentralisation of the blockchain and numerous other important characteristics. Choosing an appropriate consensus algorithm for different scenarios is currently a challenge in the implementation of blockchain applications. This paper classifies the improvement schemes of proof of stake (PoS) into three categories: PoS-based consensus algorithms, PoS- and PoW-based consensus algorithms, and PoS- and BFT-based consensus algorithms. First, the study introduces the PoS and PoS consensus algorithm variants and then summarises the core ideas, effects, advantages, and disadvantages of these algorithms. Subsequently, the performances of the improved algorithms are compared. Finally, the main improved methods are summarised, and the most common network security attacks are discussed. The study lays a foundation for the main improvement directions of PoS in the future, hoping to provide a reference for researchers to help them select and design consensus algorithms in different application scenarios while also helping the evolution of consensus algorithms and the implementation of blockchain applications.
Improvements in fabrication devices such as 3D printers are becoming possible for personal fabrication to freely fabricate any products. To clarify who is liable for the product, the fabricator should keep the fabrication history in an immutable and sustainably accessible manner. In this paper, we propose a new scheme, "Fabchain," that can record the fabrication history in such a manner. By utilizing a scheme that employs a blockchain as an audit-able communication channel, Fabchain manages print jobs for the fabricator's 3D printer over the blockchain, while maintaining a history of a print job. We implemented Fabchain on Ethereum and evaluated the performance for recording a print job. Our results demonstrate that Fabchain can complete communication of a print job sequence in less than 1 minute on the Ethereum test network. We conclude that Fabchain can manage a print job in a reasonable duration for 3D printing, while satisfying the requirements for immutability and sustainability.
With the development of advanced information and communication technology, the traditional centralized cloud architecture cannot satisfy the exploding demand for data exchange in Internet of Vehicle (IoV) systems. Moreover, the traditional centralized architecture of the vehicular network has the potential risk of a single point of failure and lacks autonomy since the system highly relies on a trusted third party (TTP) to provide identity management. Fortunately, the emergence of blockchain technology provides a potential direction to address these problems. However, there are still some problems existing in the construction of an efficient blockchain system in IoV systems, such as the dynamic network topology and limited resources. In this paper, we propose a hierarchical resource scheduling scheme for blockchain-enabled IoV systems that improves the performance of the blockchain-enabled IoV system by efficiently allocating computational resources. The superiority of the proposed method is fully demonstrated by comparing it with existing baseline methods.
A dashboard camera (Dashcam) is attached to the front or rear of a vehicle to record images and video. As it is effective in crime prevention and accident management and it can also be used as learning data for Traffic Accident Detection technology for Autonomous Vehicles the use of Dashcam is increasing. However, the video data is stored on a memory card or a cloud server, so there is a high possibility of data loss and forgery. Although it is possible to prevent forgery and falsification using distributed storage based on blockchain technology, the authenticity and privacy of the image data stored in the blockchain cannot be guaranteed. In this study, to solve this problem, we propose a multi-signature-based access control method by grouping and storing video data of multiple vehicles based on GPS (Global Positioning System) data. To ensure the privacy of the video data stored in the blockchain, only users uploading video belonging to the relevant GPS can access nearby Dashcam videos. Through these experimental results, it show that Experimental results proposed method can maintain low latency in large-scale request environment to the privacy and reach data management efficiently in a distributed file system. According to our experiments, the dashcam video data distributed storage latency was fast enough, with an average of 25 ms for uploads and less than 15 ms for downloads. The signature generation time is 10ms, and the verification time required for access control is also less than 100 ms, which is the same even if the number of nodes increases, so scalability is not affected. The blockchain transaction processing took about 2 seconds, but it does not affect the V2V network. Also, client registration time does not affect performance.
Due to aggressive urbanization (with population size), waste increases exponentially, resulting in environmental damage. Even though it looks challenging, such an issue can be controlled if we can reuse them. To handle this, in our work, we design a machine learning and blockchain-oriented system that identifies thewaste objects/products and recommends to the user multiple ’Do-It-Yourself’ (DIY) ideas to reuse or recycle. Blockchain records every transaction in the shared ledger to enable transaction verifiability and supports better decision-making. In this study, a Deep Neural Network (DNN) trained on about 11700 images is developed using ResNet50 architecture for object recognition (training accuracy of 94%).We deploy several smart contracts in the Hyperledger Fabric (HF) blockchain platform to validate recommended DIY ideas by blockchain network members. HF is a decentralized ledger technology platform that executes the deployed smart contracts in a secured Docker container to initialize and manage the ledger state. The complete model is delivered on a web platform using Flask, where our recommendation system works on a web scraping script written using Python. Fetching DIY ideas using web-scraping takes nearly 1 second on a desktop machine with an Intel Core-i7 processor with 8 cores, 16 GB RAM, installed with Ubuntu 18.04 64-bit operating system, and Python 3.6 package. Further, we evaluate blockchain-based smart contracts’ latencies and throughput performances using the hyperledger caliper benchmark. To the best of our knowledge, this is the first work that integrates blockchain technology and deep learning for the DIY recommender system.
The emergence of technological innovations in disciplines such as Artificial Intelligence (AI) and the Internet of Things (IOT) has introduced opportunities to enhance the traditional user experience. The potential of these opportunities has yet to be fully explored particularly within the cultural heritage sector where immersive technologies can benefit both the user and the heritage site. A potentially unforgettable user experience can be offered in an immersive environment and these technologies can also be used to rebuild locations under threat to ensure they can be accessed in the future (Garlandini, 2021). The intention of this paper is to critically analyse the emergence of Industry 5.0 and the implementation of personalisation in a machine learning system. It is important to thoroughly evaluate the aspects of AI technologies and the IOT that can be used to support personalisation. An element of blockchain technology known as Non-Fungible Tokens (NFTs) which was developed in the recent past may have the potential to address ongoing challenges in digital curation and this research paper will provide an evaluation of this technology. It is crucial for all the technologies mentioned to work together to produce a system that aligns with the traditional human-centred philosophy and is inclusive to all participants.