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.

Novelty Detection in Human Behavior through Analysis of Energy Utilization

2013 ◽  
pp. 65-85 ◽  
Author(s):  
Chao Chen ◽  
Diane J. Cook
Keyword(s):  
Energy Consumption ◽  
Human Behavior ◽  
Novelty Detection ◽  
Electricity Consumption ◽  
Energy Utilization ◽  
Smart Environments ◽  
Data Sets ◽  
Smart Environment ◽  
Energy Data ◽  
Using Data

The value of smart environments in understanding and monitoring human behavior has become increasingly obvious in the past few years. Using data collected from sensors in these environments, scientists have been able to recognize activities that residents perform and use the information to provide context-aware services and information. However, less attention has been paid to monitoring and analyzing energy usage in smart homes, despite the fact that electricity consumption in homes has grown dramatically. In this chapter, the authors demonstrate how energy consumption relates to human activity through verifying that energy consumption can be predicted based on the activity that is being performed. The authors then automatically identify novelties in human behavior by recognizing outliers in energy consumption generated by the residents in a smart environment. To validate these approaches, they use real energy data collected in their CASAS smart apartment testbed and analyze the results for two different data sets collected in this smart home.

Contemporary Energy Management Systems and Future Prospects

2021 ◽  
pp. 1984-2013
Author(s):  
Amir Manzoor
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
User Participation ◽  
Energy Utilization ◽  
Security And Privacy ◽  
Management Systems ◽  
Future Research ◽  
Energy Management Systems ◽  
Research Areas ◽  
Emerging Trends

The transformation of electric grid into smart grid has improved management of available resources and increased energy efficiency. Energy management systems (EMS) play an important role in enhancing user participation in control of energy management. Using such systems, consumers can obtain information about their energy consumption patterns and shape their energy consumption behaviors for efficient energy utilization. Contemporary EMS utilizes advanced analytics and ICT to provide consumers actionable feedback and control of energy management. These systems provide high availability, an easy-to-use user interface, security, and privacy. This chapter explores the contemporary EMS, their applications, classifications, standards, and frameworks. The chapter defines a set of requirements for EMS and provides feature comparison of various EMS. The chapter also discusses emerging trends and future research areas in EMS.

Contemporary Energy Management Systems and Future Prospects

2016 ◽  
pp. 265-292
Author(s):  
Amir Manzoor
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
User Participation ◽  
Energy Utilization ◽  
Security And Privacy ◽  
Management Systems ◽  
Future Research ◽  
Energy Management Systems ◽  
Research Areas ◽  
Emerging Trends

The transformation of electric grid into smart grid has improved management of available resources and increased energy efficiency. Energy management systems (EMS) play an important role in enhancing user participation in control of energy management. Using such systems, consumers can obtain information about their energy consumption patterns and shape their energy consumption behaviors for efficient energy utilization. Contemporary EMS utilizes advanced analytics and ICT to provide consumers actionable feedback and control of energy management. These systems provide high availability, an easy-to-use user interface, security, and privacy. This chapter explores the contemporary EMS, their applications, classifications, standards, and frameworks. The chapter defines a set of requirements for EMS and provides feature comparison of various EMS. The chapter also discusses emerging trends and future research areas in EMS.

scholarly journals Towards a Secure and Scalable IoT Infrastructure: A Pilot Deployment for a Smart Water Monitoring System

Technologies ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 50
Author(s):  
Anthony Overmars ◽  
Sitalakshmi Venkatraman
Keyword(s):  
Monitoring System ◽  
Low Cost ◽  
Water Monitoring ◽  
Security And Privacy ◽  
Security Model ◽  
Smart Environment ◽  
Iot Security ◽  
Security Controls ◽  
Smart Water ◽  
Iot Devices

Recent growth in the Internet of Things (IoT) looks promising for realizing a smart environment of the future. However, concerns about the security of IoT devices are escalating as they are inherently constrained by limited resources, heterogeneity, and lack of standard security controls or protocols. Due to their inability to support state-of-the-art secure network protocols and defense mechanisms, standard security solutions are unsuitable for dynamic IoT environments that require large and smart IoT infrastructure deployments. At present, the IoT based smart environment deployments predominantly use cloud-centric approaches to enable continuous and on-demand data exchange that leads to further security and privacy risks. While standard security protocols, such as Virtual Private Networks (VPNs), have been explored for certain IoT environments recently, the implementation models reported have several variations and are not practically scalable for any dynamically scalable IoT deployment. This paper addresses current drawbacks in providing the required flexibility, interoperability, scalability, and low-cost practical viability of a secure IoT infrastructure. We propose an adaptive end-to-end security model that supports the defense requirements for a scalable IoT infrastructure. With low-cost embedded controllers, such as the Raspberry Pi, allowing for the convergence of more sophisticated networking protocols to be embedded at the IoT monitoring interface, we propose a scalable IoT security model integrating both the IoT devices and the controller as one embedded device. Our approach is unique, with a focus on the integration of a security protocol at the embedded interface. In addition, we demonstrate a prototype implementation of our IoT security model for a smart water monitoring system. We believe that our modest first step would instill future research interests in this direction.

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