Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

Extending sensor networks into the cloud using Amazon web services

Sensor networks provide a method of collecting environmental data for use in a variety of distributed applications. However, to date, limited support has been provided for the development of integrated environmental monitoring and modeling applications. Specifically, environmental dynamism makes it difficult to provide computational resources that are sufficient to deal with changing environmental conditions. This paper argues that the Cloud Computing model is a good fit with the dynamic computational requirements of environmental monitoring and modeling. We demonstrate that Amazon EC2 can meet the dynamic computational needs of environmental applications. We also demonstrate that EC2 can be integrated with existing sensor network technologies to offer an end-to-end environmental monitoring and modeling solution

Experiences and issues for environmental engineering sensor network deployments

Sensor network research is a large and growing area of academic effort, examining technological and deployment issues in the area of environmental monitoring. These technologies are used by environmental engineers and scientists to monitor a multiplicity of environments and services, and, specific to this paper, energy and water supplied to the built environment. Although the technology is developed by Computer Science specialists, the use and deployment is traditionally performed by environmental engineers. This paper examines deployment from the perspectives of environmental engineers and scientists and asks what computer scientists can do to improve the process. The paper uses a case study to demonstrate the agile operation of WSNs within the Cloud Computing infrastructure, and thus the demand-driven, collaboration-intense paradigm of Digital Ecosystems in Complex Environments

Experiences and issues for environmental science sensor network deployments

Sensor network research is a large and growing area of academic effort, examining technological and deployment issues in the area of environmental monitoring. These technologies are used by environmental engineers and scientists to monitor a multiplicity of environments and services, and, specific to this paper, energy and water supplied to the built environment. Although the technology is developed by Computer Science specialists, the use and deployment is traditionally performed by environmental engineers. This paper examines deployment from the perspectives of environmental engineers and scientists and asks what computer scientists can do to improve the process. The paper uses a case study to demonstrate the agile operation of WSNs within the Cloud Computing infrastructure, and thus the demand-driven, collaboration-intense paradigm of Digital Ecosystems in Complex Environments

Recent advances in industrial wireless sensor networks towards efficient management in IoT

With the accelerated development of Internet-of- Things (IoT), wireless sensor networks (WSN) are gaining importance in the continued advancement of information and communication technologies, and have been connected and integrated with Internet in vast industrial applications. However, given the fact that most wireless sensor devices are resource constrained and operate on batteries, the communication overhead and power consumption are therefore important issues for wireless sensor networks design. In order to efficiently manage these wireless sensor devices in a unified manner, the industrial authorities should be able to provide a network infrastructure supporting various WSN applications and services that facilitate the management of sensor-equipped real-world entities. This paper presents an overview of industrial ecosystem, technical architecture, industrial device management standards and our latest research activity in developing a WSN management system. The key approach to enable efficient and reliable management of WSN within such an infrastructure is a cross layer design of lightweight and cloud-based RESTful web service