Blockchain + IoT sensor network to measure, evaluate and incentivize personal environmental accounting and efficient energy use in indoor spaces

Ma, Nan; Waegel, Alex; Hakkarainen, Max; Braham, William W.; Glass, Lior; Aviv, Dorit

doi:10.1016/j.apenergy.2022.120443

Cited by 15 publications

(3 citation statements)

References 66 publications

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“…Ma et al [9] have contributed significantly to the advancement of real-time carbon accounting and energy monitoring by highlighting the essential roles of carbon intensity (CI), overall carbon optimization (OCO), and marginal carbon optimization (MCO) in evaluating energy use and its environmental impact. Their integration of IoT sensors with blockchain technology has revolutionized data acquisition and management, improving the transparency and scalability of energy monitoring systems.…”

Section: Healthcare Iotmentioning

confidence: 99%

Enhancing Industrial IoT Network Security through Blockchain Integration

Bobde,

Narayanan,

Jati

et al. 2024

Electronics

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In the rapidly evolving landscape of industrial ecosystems, Industrial IoT networks face increasing security challenges. Traditional security methods often struggle to protect these networks adequately, posing risks to data integrity, confidentiality, and access control. Our research introduces a methodology that leverages blockchain technology to enhance the security and trustworthiness of IoT networks. This approach starts with sensor nodes collecting and compressing data, followed by encryption using the ChaCha20-Poly1305 algorithm and transmission to local aggregators. A crucial element of our system is the private blockchain gateway, which processes and classifies data based on confidentiality levels, determining their storage in cloud servers or the Interplanetary File System for enhanced security. The system’s integrity and authenticity are further reinforced through the proof of authority consensus mechanism. This system employs Zero Knowledge Proof challenges for device authorization, optimizing data retrieval while maintaining a delicate balance between security and accessibility. Our methodology contributes to mitigating vulnerabilities in Industrial IoT networks and is part of a broader effort to advance the security and operational efficiency of these systems. It reflects an understanding of the diverse and evolving challenges in IoT security, emphasizing the need for continuous innovation and adaptation in this dynamic field.

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Section: Healthcare Iotmentioning

confidence: 99%

Enhancing Industrial IoT Network Security through Blockchain Integration

Bobde,

Narayanan,

Jati

et al. 2024

Electronics

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“…Further developments to leverage the massive data collected from IoT devices can be seen through the implementation of AI techniques to forecast energy consumption, providing insights to users and most importantly reducing its cost implications [41,42].…”

Section: Conceptual Background 21 Application Of Iot In the Built Env...mentioning

confidence: 99%

Digital twin with Machine learning for predictive monitoring of CO2 equivalent from existing buildings

Arva¹,

Elghaish

Zoher³

2023

Energy and Buildings

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“…The IoTs allow the exchange of information that captures carbon emission and energy consumption data in real time across different platforms and enable the integration of this environmental data with BIM models [101]. Further, AI technology can use vast amounts of data collected from IoTs platforms to predict construction energy consumption [102]. The integration of BIM with the IoTs, AI, and cloud computing can also enable efficient building operations and sustainable development [103].…”

Section: Challenges Of Integrating Bim and Lcamentioning

confidence: 99%

Current Status and Future Directions of Building Information Modeling for Low-Carbon Buildings

Liu,

Chen,

et al. 2023

Energies

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In recent years, with the intensification of climate change, the development of low-carbon buildings (LCBs) has gained great momentum, and building information modeling (BIM) is perceived as the most promising path. However, systematic integration, review, and analysis of research in the field of BIM for LCBs has been lacking, which may hinder the potential of BIM in assisting the achievement of the goal of LCBs. Therefore, this study explores the current research status of BIM for LCBs and the directions for further investigation. A hybrid literature review method was utilized, which consisted of quantitative and qualitative analyses. Firstly, a quantitative bibliometric analysis was conducted on 158 studies searched from the Web of Science core collection. The most influential institutions, journals, studies, and keywords were identified. The most often used terms were BIM, life-cycle assessment (LCA), design, construction, digital technologies (DTs), life cycle, and integration. Secondly, a systematic qualitative analysis was conducted of 117 carefully selected studies to identify the research focus of different stages (e.g., design, construction, operation, and demolition) of BIM for LCBs. The results showed that studies pertaining to BIM for LCBs mostly took a whole life-cycle perspective, followed by a focus on the design stage, while the volumes of studies focusing on BIM for LCBs in the operation and demolition stages were relatively small. Currently, research focuses on how the latest methods and technologies can be utilized to help reduce carbon dioxide emissions over the life cycle of a building, e.g., BIM-LCA and BIM combined with DTs. Lastly, the challenges and prospects of integrating BIM with LCA and emerging DTs for LCBs are discussed in depth. Five topics, such as BIM-based interdisciplinary collaboration and improving and validating the BIM integrated sustainability calculation models, are proposed as future research trends. This study points out the current research hotspots and future research trends in the field and builds a solid starting point for scholars who want to devote themselves to this field. For practitioners in LCBs, the research findings could serve as a practical reference for better understanding the potential of BIM for LCBs so as to take full advantage of BIM to more effectively realize the goal of LCBs.

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Blockchain + IoT sensor network to measure, evaluate and incentivize personal environmental accounting and efficient energy use in indoor spaces

Cited by 15 publications

References 66 publications

Enhancing Industrial IoT Network Security through Blockchain Integration

Enhancing Industrial IoT Network Security through Blockchain Integration

Digital twin with Machine learning for predictive monitoring of CO2 equivalent from existing buildings

Current Status and Future Directions of Building Information Modeling for Low-Carbon Buildings

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