Data Access Mechanism to Allow Multiple Level Permissions in Energy Management Solutions Supported by IoT devices

2021 ◽  
Author(s):  
Nuno Teixeira ◽  
Luis Gomes ◽  
Zita Vale
Keyword(s):  
Energy Management ◽  
Data Access ◽  
Multiple Level ◽  
Iot Devices

scholarly journals Device-Based Security to Improve User Privacy in the Internet of Things †

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2664 ◽  
Author(s):  
Luis Belem Pacheco ◽  
Eduardo Pelinson Alchieri ◽  
Priscila Mendez Barreto
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Single Point ◽  
Data Access ◽  
Cloud Services ◽  
Sensitive Information ◽  
User Privacy ◽  
Privacy And Security ◽  
Iot Devices ◽  
And Control

The use of Internet of Things (IoT) is rapidly growing and a huge amount of data is being generated by IoT devices. Cloud computing is a natural candidate to handle this data since it has enough power and capacity to process, store and control data access. Moreover, this approach brings several benefits to the IoT, such as the aggregation of all IoT data in a common place and the use of cloud services to consume this data and provide useful applications. However, enforcing user privacy when sending sensitive information to the cloud is a challenge. This work presents and evaluates an architecture to provide privacy in the integration of IoT and cloud computing. The proposed architecture, called PROTeCt—Privacy aRquitecture for integratiOn of internet of Things and Cloud computing, improves user privacy by implementing privacy enforcement at the IoT devices instead of at the gateway, as is usually done. Consequently, the proposed approach improves both system security and fault tolerance, since it removes the single point of failure (gateway). The proposed architecture is evaluated through an analytical analysis and simulations with severely constrained devices, where delay and energy consumption are evaluated and compared to other architectures. The obtained results show the practical feasibility of the proposed solutions and demonstrate that the overheads introduced in the IoT devices are worthwhile considering the increased level of privacy and security.

Combining BIM, GIS, and IoT to Foster Energy Management and Simulation in Smart Cities

2021 ◽  
pp. 425-447
Author(s):  
Edoardo Patti ◽  
Francesco G. Brundu ◽  
Andrea Bellagarda ◽  
Lorenzo Bottaccioli ◽  
Niccolò Rapetti ◽  
...  
Keyword(s):  
Energy Management ◽  
Smart Cities ◽  
Control Strategies ◽  
Control Policy ◽  
Information Model ◽  
Environmental Data ◽  
Software Infrastructure ◽  
Heterogeneous Information ◽  
Building Information ◽  
Iot Devices

This chapter presents a novel distributed software infrastructure to enable energy management and simulation of novel control strategies in smart cities. In this context, the following heterogeneous information, describing the different entities in a city, needs to be taken into account to form a unified district information model: internet-of-things (IoT) devices, building information model, system information model, and georeferenced information system. IoT devices are crucial to monitor in (near-) real-time both building energy trends and environmental data. Thus, the proposed solution fulfills the integration and interoperability of such data sources providing also a correlation among them. Such correlation is the key feature to unlock management and simulation of novel energy policies aimed at optimizing the energy usage accounting also for its impact on building comfort. The platform has been deployed in a real-world district and a novel control policy for the heating distribution network has been developed and tested. Finally, experimental results are presented and discussed.

scholarly journals Secure and Intelligent Energy Data Management Scheme for Smart IoT Devices

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Tianqi Zhou ◽  
Jian Shen ◽  
Sai Ji ◽  
Yongjun Ren ◽  
Leiming Yan
Keyword(s):  
Renewable Energy ◽  
Data Management ◽  
Energy Management ◽  
Energy Utilization ◽  
Security And Privacy ◽  
Smart Environment ◽  
Energy Data ◽  
Management Scheme ◽  
High Efficient ◽  
Iot Devices

The renewable energy plays an increasingly important role in many fields such as lighting, automobile, and electric power. In order to make full use of the renewable energy, various smart Internet of Thing (IoT) devices are deployed. However, in the field of energy management, the two-way mismatch between the demand and the supply of the renewable energy will greatly affect the efficiency of the renewable energy. In addition, the security threat of the energy data and the privacy leakage of the user may hinder the further development of smart IoT devices. Therefore, how to achieve consistency and balance between the demand and the renewable energy supply and how to guarantee the security and privacy of smart IoT devices become the key problems of the energy-efficient smart environment. In this paper, a secure and intelligent energy data management scheme for smart IoT devices is proposed. It is worth noting that, with the help of artificial intelligence (AI) technologies and secure cryptography primitives, the proposed scheme realizes high-efficient and secure energy utilization in a smart environment. Specifically, the proposed scheme aims at improving the efficiency of the energy utilization in the multidimensions of a smart environment. In order to realize the fine-grain energy management of smart IoT devices, strategies of three different dimensions are considered and realized in the proposed scheme. Moreover, technologies in AI are applied and integrated into the energy management scheme. The analysis shows that the proposed scheme can make full use of the renewable energy in smart IoT devices.

scholarly journals A Smart Autonomous Time- and Frequency-Domain Analysis Current Sensor-Based Power Meter Prototype Developed over Fog-Cloud Analytics for Demand-Side Management

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4443 ◽  
Author(s):  
Yung-Yao Chen ◽  
Yu-Hsiu Lin
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Electrical Energy ◽  
Demand Side Management ◽  
Current Sensor ◽  
The Internet ◽  
Load Identification ◽  
Demand Side ◽  
Power Meter ◽  
Iot Devices

Electrical energy management, or demand-side management (DSM), in a smart grid is very important for electrical energy savings. With the high penetration rate of the Internet of Things (IoT) paradigm in modern society, IoT-oriented electrical energy management systems (EMSs) in DSM are capable of skillfully monitoring the energy consumption of electrical appliances. While many of today’s IoT devices used in EMSs take advantage of cloud analytics, IoT manufacturers and application developers are devoting themselves to novel IoT devices developed at the edge of the Internet. In this study, a smart autonomous time and frequency analysis current sensor-based power meter prototype, a novel IoT end device, in an edge analytics-based artificial intelligence (AI) across IoT (AIoT) architecture launched with cloud analytics is developed. The prototype has assembled hardware and software to be developed over fog-cloud analytics for DSM in a smart grid. Advanced AI well trained offline in cloud analytics is autonomously and automatically deployed onsite on the prototype as edge analytics at the edge of the Internet for online load identification in DSM. In this study, auto-labeling, or online load identification, of electrical appliances monitored by the developed prototype in the launched edge analytics-based AIoT architecture is experimentally demonstrated. As the proof-of-concept demonstration of the prototype shows, the methodology in this study is feasible and workable.

EEB Project System Integration and Technology Sperimentation Matrix

2021 ◽  
pp. 196-218
Author(s):  
Francesca Maria Ugliotti
Keyword(s):  
Decision Making ◽  
Energy Management ◽  
System Integration ◽  
Smart Cities ◽  
Three Dimensional ◽  
Semantic Data ◽  
Energy Efficient Buildings ◽  
Digital Twins ◽  
Urban Modelling ◽  
Iot Devices

Today an increasing number of cities are equipping themselves with three-dimensional urban modelling and simulation platforms for energy management to integrate both spatial and semantic data for enabling better decision-making. The work presented in this chapter is the result of the study carried out by Politecnico di Torino within the Energy Efficient Buildings (EEB) project. Collected data on urban and building scale are managed in specialized, independent, and heterogeneous domains such as GIS, BIM, and IoT devices for energy and electrical monitoring. Possible relationships among these datasets in the perspective of system integration have been carried out according to a rich matrix of experimentations. Specific tools, including innovative visualization technologies and web services, are put in place to allow final users to benefit from this data. The infrastructure is intended to establish a common interoperable ground among heterogeneous networks to achieve the goal of smart cities digital twins.

Achieving adaptively secure data access control with privacy protection for lightweight IoT devices

2021 ◽  
Vol 64 (6) ◽  
Author(s):  
Zhitao Guan ◽  
Wenti Yang ◽  
Liehuang Zhu ◽  
Longfei Wu ◽  
Ruimiao Wang
Keyword(s):  
Access Control ◽  
Privacy Protection ◽  
Data Access ◽  
Data Access Control ◽  
Secure Data ◽  
Iot Devices

scholarly journals AI and Data Democratisation for Intelligent Energy Management

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4341
Author(s):  
Vangelis Marinakis ◽  
Themistoklis Koutsellis ◽  
Alexandros Nikas ◽  
Haris Doukas
Keyword(s):  
Data Sharing ◽  
Energy Management ◽  
Business Models ◽  
Data Access ◽  
Energy Sector ◽  
Regulatory Constraints ◽  
Access Problems ◽  
Near Term ◽  
The Right ◽  
Novel Applications

Despite the large number of technology-intensive organisations, their corporate know-how and underlying workforce skill are not mature enough for a successful rollout of Artificial Intelligence (AI) services in the near-term. However, things have started to change, owing to the increased adoption of data democratisation processes, and the capability offered by emerging technologies for data sharing while respecting privacy, protection, and security, as well as appropriate learning-based modelling capabilities for non-expert end-users. This is particularly evident in the energy sector. In this context, the aim of this paper is to analyse AI and data democratisation, in order to explore the strengths and challenges in terms of data access problems and data sharing, algorithmic bias, AI transparency, privacy and other regulatory constraints for AI-based decisions, as well as novel applications in different domains, giving particular emphasis on the energy sector. A data democratisation framework for intelligent energy management is presented. In doing so, it highlights the need for the democratisation of data and analytics in the energy sector, toward making data available for the right people at the right time, allowing them to make the right decisions, and eventually facilitating the adoption of decentralised, decarbonised, and democratised energy business models.

scholarly journals Towards Scalable and Efficient Architecture for Modeling Trust in IoT Environments

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2986
Author(s):  
Mustafa Ghaleb ◽  
Farag Azzedin
Keyword(s):  
Wide Spectrum ◽  
Fog Computing ◽  
Data Access ◽  
Driven Systems ◽  
Trust Modeling ◽  
Smart Surveillance ◽  
Trust Models ◽  
Cloud Environments ◽  
Iot Devices ◽  
Extensive Performance

The Internet of Services (IoS) is gaining ground where cloud environments are utilized to create, subscribe, publish, and share services. The fast and significant evolution of IoS is affecting various aspects in people’s life and is enabling a wide spectrum of services and applications ranging from smart e-health, smart homes, to smart surveillance. Building trusted IoT environments is of great importance to achieve the full benefits of IoS. In addition, building trusted IoT environments mitigates unrecoverable and unexpected damages in order to create reliable, efficient, stable, and flexible smart IoS-driven systems. Therefore, ensuring trust will provide the confidence and belief that IoT devices and consequently IoS behave as expected. Before hosting trust models, suitable architecture for Fog computing is needed to provide scalability, fast data access, simple and efficient intra-communication, load balancing, decentralization, and availability. In this article, we propose scalable and efficient Chord-based horizontal architecture. We also show how trust modeling can be mapped to our proposed architecture. Extensive performance evaluation experiments have been conducted to evaluate the performance and the feasibility and also to verify the behavior of our proposed architecture.

Sign in / Sign up

Export Citation Format

Share Document