A Review On Smart Building And Blockchain Technology

Blockchain and IoT technology have transformed smart buildings, especially in distributed renewable power systems. Blockchain IoT plays a key role in integrating renewable energy sources into smart building systems. IoT devices and sensors provide real-time data collecting and monitoring of energy use and production allowing renewable power resource management and optimization. Blockchain technology improves data security, transparency, and immutability, guaranteeing energy-related transactions and information exchange are trustworthy. A decentralised ledger system allows stakeholders to trade energy transparently and efficiently, creating a peer-to-peer energy exchange network in smart buildings and boosts energy system dependability, resilience, carbon footprint reduction, and sustainable energy practises. Thus, Blockchain IoT and smart buildings enable the creation of robust, energy-efficient ecosystems that prioritize renewable power sources, reshaping energy management and sustainability.

Intelligent Amalgamation of Blockchain Technology with Industry 4.0 to Improve Security

Smart buildings are equipped with computer systems that monitor and control diverse services such as air conditioning, indoor transportation, physical access control, and many others. Critical infrastructures like hospitals, airports, and data centers, leverage on such services to support their daily operations. However, the current popularity of smart buildings is founded on a decades-long history. Smart building systems have evolved from isolated networks using proprietary protocols to IT-integrated systems that use standardized communication protocols. They might even be connected to the Internet to allow remote building management. This transition has exposed smart buildings to a whole new set of security threats. For instance, there have been documented cases where attackers have managed to remotely disrupt the environmental conditions and physical access control of smart buildings. Due to the crucial role that smart buildings play in supporting organizations and the serious threat of cyber attacks against them, there is a pressing need to investigate how to improve their current security posture.<br/>The transfer of mature IT security solutions to smart building systems seems a natural approach to enhance their security, however, the fundamental differences between both domains often require significant adaptation effort or to develop completely new solutions. For this reason, in recent years, a growing body knowledge about smart buildings security has been developed. However, most of these solutions have focused on intrusion detection and little efforts have been made to prevent cyber attacks. An effective way to prevent cyber attacks against smart buildings is by preemptively handling security weaknesses in customized applications and configurations that run the system. Unfortunately, this is often overlooked by smart building administrators due to, e.g., lack of specialized tools, staff, and training. We identify not only a research gap regarding this important task, but also an urgent need to provide (semi-) automated tools that help overcome the limitations faced by smart building administrators. The implementation of these tools requires sophisticated methods that incorporate technical and business-related insights to handle weaknesses according to the organization’s best interest.<br/>In this thesis, we investigate how to implement the first stages of a vulnerability management process for smart building applications and configurations. Beyond just vulnerabilities, we consider the weaknesses that give rise to vulnerabilities. In particular, our contributions address the identification and assessment of security weaknesses for later remediation. These are two key activities to preemptively strengthen the security of smart buildings. The identification of weaknesses is the basis of any vulnerability management process as it provides the first insights about the current security state of a system. This is a challenging task because a deep understanding of the system’s inner workings is often needed to obtain meaningful findings. We propose two approaches to identify security weaknesses; one focused on smart building applications and another on smart building configurations. In the first case, we model the application as a graph data structure comprised of sensors, setpoints, actuators, and control function nodes. The relationships among these components reveal the architecture of the system, which can then be analyzed in the search for security weaknesses. In the second case, we look for component misconfigurations that can be observed in their behavior, i.e., the way they interact with other components in the system. Leveraging official documentation from the components’ manufacturers, we create a model of valid behavior for each of them, which is then compared with their actual behavior as observed in the network traffic. After identifying security weaknesses, we assess the sensitivity of the affected components, which is an important factor to prioritize weaknesses for later remediation. We propose a comprehensive approach to assess the sensitivity of smart building components based on technical and business-related features. The proposed methods are evaluated in real smart buildings and additional experiments are performed in testbeds and comparable simulated environments. These evaluations confirm the feasibility and effectivity of our (semi-) automated weakness identification and assessment approaches.

BackgroundResearchers have increasingly adopted AI and next-generation sequencing (NGS), revolutionizing genomics and high-throughput screening (HTS), and transforming our understanding of cellular processes and disease mechanisms. However, these advancements generate vast datasets requiring effective data stewardship and curation practices to maintain data integrity, privacy, and accessibility. This review consolidates existing knowledge on key aspects, including data governance, quality management, privacy measures, ownership, access control, accountability, traceability, curation frameworks, and storage systems.MethodsWe conducted a systematic literature search up to January 10, 2024, across PubMed, MEDLINE, EMBASE, Scopus, and additional scholarly platforms to examine recent advances and challenges in managing the vast and complex datasets generated by these technologies. Our search strategy employed structured keyword queries focused on four key thematic areas: data governance and management, curation frameworks, algorithmic bias and fairness, and data storage, all within the context of AI applications in genomics and microscopy. Using a realist synthesis methodology, we integrated insights from diverse frameworks to explore the multifaceted challenges associated with data stewardship in these domains. Three independent reviewers, who systematically categorized the information across critical themes, including data governance, quality management, security, privacy, ownership, and access control conducted data extraction and analysis. The study also examined specific AI considerations, such as algorithmic bias, model explainability, and the application of advanced cryptographic techniques. The review process included six stages, starting with an extensive search across multiple research databases, resulting in 273 documents. Screening based on broad criteria, titles, abstracts, and full texts followed this, narrowing the pool to 38 highly relevant citations.ResultsOur findings indicated that significant research was conducted in 2023 by highlighting the increasing recognition of robust data governance frameworks in AI-driven genomics and microscopy. While 36 articles extensively discussed data interoperability and sharing, AI-model explain ability and data augmentation remained underexplored, indicating significant gaps. The integration of diverse data types—ranging from sequencing and clinical data to proteomic and imaging data—highlighted the complexity and expansive scope of AI applications in these fields. The current challenges identified in AI-based data stewardship and curation practices are lack of infrastructure and cost optimization, ethical and privacy considerations, access control and sharing mechanisms, large scale data handling and analysis and transparent data-sharing policies and practice. Proposed solutions to address issues related to data quality, privacy, and bias management include advanced cryptographic techniques, federated learning, and blockchain technology. Robust data governance measures, such as GA4GH standards, DUO versioning, and attribute-based access control, are essential for ensuring data integrity, security, and ethical use. The study also emphasized the critical role of Data Management Plans (DMPs), meticulous metadata curation, and advanced cryptographic techniques in mitigating risks related to data security and identifiability. Despite advancements, significant challenges persisted in balancing data ownership with research accessibility, integrating heterogeneous data sources, ensuring platform interoperability, and maintaining data quality. Ongoing risks of unauthorized access and data breaches underscored the need for continuous innovation in data management practices and stricter adherence to legal and ethical standards.ConclusionsThese findings explored the current practices and challenges in data stewardship, offering a roadmap for strengthening the governance, security, and ethical use of AI in genomics and microscopy. While robust governance frameworks and ethical practices have established a foundation for data integrity and transparency, there remains an urgent need for collaborative efforts to develop interoperable platforms and transparent data-sharing policies. Additionally, evolving legal and ethical frameworks will be crucial to addressing emerging challenges posed by AI technologies. Fostering transparency, accountability, and ethical responsibility within the research community will be key to ensuring trust and driving ethically sound scientific advancements.

The convergence of blockchain, artificial intelligence (AI), and cloud computing is catalyzing a paradigm shift in developing secure, intelligent, and scalable digital infrastructures. This triad of technologies is increasingly utilized to improve performance, transparency, and trust in engineering-driven and socio-technical environments. This study systematically reviews the evolution, integration strategies, and applications of blockchain, AI, and cloud computing in digital ecosystems. The analysis is based on 108 peer-reviewed studies spanning the years 2012 to 2025. A comprehensive literature analysis was conducted to identify trends, synergies, and sector-specific implementations of these systems. The review explores how their integration supports real-world engineering and operational use cases. Blockchain contributes to decentralized architectures, secure data exchange, and identity verification. AI supports adaptive behavior, autonomous decision-making, and predictive analytics. Cloud computing offers the scalable infrastructure necessary for deployment. Key challenges addressed include interoperability, latency, security trade-offs, and resource allocation. Use cases in digital finance, supply chain management, and industrial automation demonstrate the effectiveness of this integration in building resilient, ethically aligned, and high-performance infrastructures. The findings offer valuable insights and technical considerations for engineers and architects seeking to design next-generation cyber-physical systems that are secure, intelligent, and socially responsive. Clinical Trial Number Not applicable. This article accentuates the extensive use of blockchain, cloud computing, and AI principles, emphasizing their crucial significance in the contemporary digital environment and paths in which blockchain technology may be employed to automate financial transactions, enhance the security of personal data and records, facilitate cross-border transactions, verify identities, execute smart contracts, utilize cryptocurrencies, and manage supply chains. This research systematically assesses the development and practical application of blockchain, cloud computing, and artificial intelligence technologies over the past decade. This study primarily focuses on monitoring the progress, practical applications, and benefits of blockchain technology in the context of financial transactions. This article probes the symbiotic relationship between artificial intelligence, cloud and blockchain technology, analyzing the evolution and fundamental concepts of their integration from 2012 to 2025. This paper also presents a detailed analysis of 108 research works acquitted over the past decade. The study provides a comprehensive examination of the current state and fundamental principles related to the integration of artificial intelligence, cloud, and blockchain technology. This paper offers a comprehensive analysis of the major obstacles confronted by blockchain technology, examining its wide-ranging applications over several industries and its socko role in transaction systems and the domain of cryptocurrencies.

Blockchain technology is evolving across the globe and is being looked upon as a definite part of the future. Blockchain is often associated with bitcoin and finance’s domain. But over the last decade, this backend technology to bitcoin has spread its association in almost all domains that we can think of. Further to this, smart contracts are making the blockchain ecosystem better. Other evolving technologies like Internet-of-things, Industrial Internet-of things, Cyber physical systems are also making their onset on the global platform. Smart buildings link Internet of-things connectivity, sensors and the cloud to remotely supervise and assure efficient heating- air conditioning, lighting and security systems etc to improve efficiency and overall sustainability. The global buildings sector over the next 40 years is expected to add 230 billion square meters of fresh construction, i.e., adding the equivalent of Paris every week. Thus integrating these technologies right at the onset, before they grow in isolation, is a coveted need today. This paper proposes a prototype to simulate architecture and discusses how blockchain-enabled smart buildings can further expedite automation, security and transparency. For an apprehension purpose, the paper focuses on smart contracts enabled repairs and service in smart buildings.

In traditional schedule, there are problems such as large forecast errors and low degree of decentralization. As the basic distributed database technology, the blockchain technology can improve the accuracy of schedule and the transparency of data if it's introduced into the traditional schedule. Therefore, based on the blockchain technology, a park microgrid scheduling model is established in this paper, where the minimum operating cost is the objective function, the power balance, the output limitation, the climbing limitation and the battery constraint are the constraints. Mixed integer programming algorithm and the GUROBI solver are used to solve the proposed model, which can effectively reduce the operating cost of the park microgrid and improve the transparency of the scheduling data. Finally, a typical park microgrid case is used to prove the feasibility of the model and solution.

With the rapid growth of digital data and inter-connected devices, the integration of blockchain and Internet of Things technology offers a promising chance to revolutionize data management approaches. With today's global connectivity, the management and securing of ever-increasing amounts the amount of data produced by Internet of Things (IoT) devices is becoming an increasing concern. This study investigates a new solution to address such a concern by integrating blockchain technology into IoT systems. The aim is to develop a strong framework that takes advantage of the decentralized and secure character of blockchain and the wall-to-wall connectivity offered by the IoT. This integration is intended to address important needs such as data integrity, The integration aims to tackle crucial issues like data integrity, privacy, and unauthorized access. With the connectivity and sensing capabilities of the IoT, along with the blockchain technology of decentralized consensus and immutable ledgers, businesses are able to develop secure systems to retrieve, transfer, and store such data. In the experiments conducted on the Ethereum blockchain platform, it has been found that the blockchain and IoT technology solution not only secures data but also facilitates information management. The experiment results demonstrate that the proposed solution is able to protect against tampering, increase the transparency of transactions, and to minimize the chances of unauthorized access. The framework is scalable and highly adaptable, and it is therefore a promising solution for various applications. This framework employs an innovative approach to ensure secure and efficient data management.

The use of blockchain technology in digital data security and efficiency in the future can provide many benefits. However, this technology also has several challenges, therefore it is necessary to continue to develop blockchain technology and find ways to overcome existing challenges. Then with all the advances in blockchain technology whose existence has been felt by most people around the world, can blockchain technology provide efficiency in terms of time and cost? Does blockchain technology guarantee higher data security? Are there challenges faced by blockchain technology? What are the challenges faced by blockchain technology? How to deal with the challenges of this blockchain technology? The purpose of this writing is, It is hoped that this writing can explain about blockchain technology, the use of blockchain technology, how blockchain technology systems work, the challenges of blockchain technology, in digital data security, and the efficiency of blockchain technology in the future. So, it is hoped that this research can provide a better understanding of blockchain technology and the potential development of blockchain technology in the future. In this study, the method we will use is the Systematic Literature Review (SLR) method. It is hoped that by using this method blockchain research can get concrete or justifiable evidence so that the findings will be obtained from the results of the experts that were developed.

Designing smart building IoT applications is a complex task. It requires efficiently integrating a broad number of heterogeneous, low-resource devices that adopt lightweight strategies. IoT frameworks, especially if they are standard-based, may help designers to scaffold the applications. OpenFog, established as IEEE 1934 standard, promotes the use of free open source (FOS) technologies and has been identified for use in smart buildings. However, smart building systems may present vulnerabilities, which can put their integrity at risk. Adopting state-of-the-art security mechanisms in this domain is critical but not trivial. It complicates the design and operation of the applications, increasing the cost of the deployed systems. In addition, difficulties may arise in finding qualified cybersecurity personnel. OpenFog identifies the security requirements of the applications, although it does not describe clearly how to implement them. This article presents a scalable architecture, based on the OpenFog reference architecture, to provide security by design in buildings of different sizes. It adopts FOS technologies over low-cost IoT devices. Moreover, it presents guidelines to help developers create secure applications, even if they are not security experts. It also proposes a selection of technologies in different layers to achieve the security dimensions defined in the X.805 ITU-T recommendation. A proof-of-concept Indoor Environment Quality (IEQ) system, based on low-cost smart nodes, was deployed in the Faculty of Engineering of Vitoria-Gasteiz to illustrate the implementation of the presented approach. The operation of the IEQ system was analyzed using software tools frequently used to find vulnerabilities in IoT applications. The use of state-of-the-art security mechanisms such as encryption, certificates, protocol selection and network partitioning/configuration in the OpenFog-based architecture improves smart building security.

The integration of blockchain technology in biomedical diagnostics offers a promising solution to the challenges of data security and privacy in infectious disease surveillance. As the digitalization of healthcare systems accelerates, the need to protect sensitive health information becomes increasingly critical. Blockchain, with its decentralized and immutable nature, provides a robust framework for ensuring the integrity and confidentiality of biomedical data. This abstract explores how blockchain technology can be leveraged to enhance data security and privacy in the context of infectious disease surveillance, where rapid and accurate data sharing is essential for effective public health responses. Infectious disease surveillance relies on the collection, analysis, and dissemination of large volumes of data, often shared across multiple institutions and geographical regions. Traditional systems for managing this data are vulnerable to breaches, unauthorized access, and data tampering, which can compromise public health efforts and patient privacy. Blockchain technology addresses these vulnerabilities by enabling secure, transparent, and tamper-proof data exchanges. Each transaction or data entry is recorded in a distributed ledger, accessible only to authorized participants, thus ensuring that the data remains secure and unaltered. Moreover, blockchain’s inherent transparency allows for real-time monitoring and auditing of data flows, which is crucial in the timely detection and response to infectious disease outbreaks. The use of smart contracts within blockchain networks further enhances the automation and efficiency of data management, ensuring that data is only accessed and shared according to predefined rules and conditions. This not only safeguards patient privacy but also builds trust among stakeholders, including patients, healthcare providers, and public health authorities. In conclusion, the integration of blockchain technology in biomedical diagnostics presents a transformative approach to addressing the critical issues of data security and privacy in infectious disease surveillance. By leveraging blockchain's unique features, healthcare systems can ensure that sensitive diagnostic data is protected, thus supporting more effective and secure public health interventions in the fight against infectious diseases. Keywords: Blockchain, Biomedical Diagnostics, Data Security, Privacy, Infectious Disease Surveillance.

Today, the Blockchain Technology has been widely explored and continuously revolutionising many sectors around the world, including construction industry. Construction industry need blockchain technology to improve the current limitation of centralised technology in its various project life-cycle. In this paper, we presented literature review, aimed to identify the potentials of Blockchain applications in construction industry. This paper also reviewed the unique features behind the blockchain technology which trigger its capabilities in construction industry. Paper further discussed the implications of the blockchain application if it were adopted in construction industry. In short, Blockchain technology is still relatively new in construction industry and further deep research is needed to develop real life on-hand application for construction industry in near future.

In the article was substantiated the essence of blockchain technology, examines its role, significance and directions of use in various spheres of public life. It has been established that the reason for the widespread use of blockchain to optimize business processes in various fields of activity lies in the advantages of this innovative technology, in particular, decentralization, transparency and security of data storage through the use of cryptographic information security mechanisms. At the same time, it was found that blockchain technology, despite its advantages, has disadvantages associated with the high network energy consumption, insufficient data storage capacity, scalability problems, lack of standardization and legal regulation of its implementation in various sectors of the economy. It is substantiated that one of the most acceptable business processes for using blockchain is accounting, since this technology is based on the double entry method, known in accounting practice, in which each transaction is recorded twice in the same amount for each of the parties to the transaction. It was found that the use of blockchain technology leads to the emergence of the so-called triple-entry accounting method. It is substantiated that the introduction of blockchain technology into accounting practice will create the prerequisites for optimizing a number of routine accounting processes, save resources on accounting, ensure accuracy, transparency and security of data, reduce the risk of distortion of accounting information and will build trust in the accounting institution. Taking into account the functionality of blockchain technology, possible directions for its use in the field of accounting are proposed, in particular for maintaining operational accounting in real time, accounting for accounts payable and receivable, accounting for the movement of the assets within an enterprise, carrying out a multilateral audit of transactions by all participants with access to blockchain networks.

In an era of rapid technological development coupled with an increasing awareness of environmental sustainability concerns, implementing smart building systems has become one of the main focuses in efforts to improve energy efficiency. Biophilic architecture integrates sunlight, vegetation, and airflow to enhance human well-being. Smart building systems utilize sensor technology, automated controls, and data analysis to optimize energy use and operational efficiency. The collaboration between biophilic concepts in building design and AI technology in smart building systems is a challenging bridge connecting technology with natural elements. This research investigates how integrating these concepts can enhance energy efficiency in modern buildings while considering user comfort. The research method used is a literature analysis related to smart building systems, biophilic architecture concepts, and case studies of buildings that apply these two topics. Data was obtained from various sources including scientific journals, books, and related technical documents. The results show that the integration of smart building systems with the application of biophilic architecture concepts has great potential to improve energy efficiency while still paying attention to the comfort of its users.

Building energy efficiency is a very effective way of energy-saving of green house, and intelligent technology is also a very important means of building energy efficiency. However, how the intelligent building energy-saving, due to the appropriate means of assessment was not established and no data to support. Intelligent building energy evaluation system for building energy consumption measurement, statistics, analysis and energy assessment in order to support the intelligent building energy-saving theory and data. This paper presents intelligent building in the new green building energy saving system based on CFD, and analyses intelligent building energy-saving evaluation system. The article extends the construction of intelligent content; enrich the connotation of the intelligent building, promoting intelligent building energy efficiency, with a strong use value and practical significance.