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

Efficient Data Collection in Multimedia Vehicular Sensing Platforms

Vehicles provide an ideal platform for urban sensing applications, as they can be equipped with all kinds of sensing devices that can continuously monitor the environment around the travelling vehicle. In this work we are particularly concerned with the use of vehicles as building blocks of a multimedia mobile sensor system able to capture camera snapshots of the streets to support traffic monitoring and urban surveillance tasks. However, cameras are high data-rate sensors while wireless infrastructures used for vehicular communications may face performance constraints. Thus, data redundancy mitigation is of paramount importance in such systems. To address this issue in this paper we exploit sub-modular optimisation techniques to design efficient and robust data collection schemes for multimedia vehicular sensor networks. We also explore an alternative approach for data collection that operates on longer time scales and relies only on localised decisions rather than centralised computations. We use network simulations with realistic vehicular mobility patterns to verify the performance gains of our proposed schemes compared to a baseline solution that ignores data redundancy. Simulation results show that our data collection techniques can ensure a more accurate coverage of the road network while significantly reducing the amount of transferred data

Robotic Searching for Stationary, Unknown and Transient Radio Sources

Searching for objects in physical space is one of the most important tasks for humans. Mobile sensor networks can be great tools for the task. Transient targets refer to a class of objects which are not identifiable unless momentary sensing and signaling conditions are satisfied. The transient property is often introduced by target attributes, privacy concerns, environment constraints, and sensing limitations. Transient target localization problems are challenging because the transient property is often coupled with factors such as sensing range limits, various coverage functions, constrained mobility, signal correspondence, limited number of searchers, and a vast searching region. To tackle these challenge tasks, we gradually increase complexity of the transient target localization problem such as Single Robot Single Target (SRST), Multiple Robots Single Target (MRST), Single Robot Multiple Targets (SRMT) and Multiple Robots Multiple Targets (MRMT). We propose the expected searching time (EST) as a primary metric to assess the searching ability of a single robot and the spatiotemporal probability occupancy grid (SPOG) method that captures transient characteristics of multiple targets and tracks the spatiotemporal posterior probability distribution of the target transmissions. Besides, we introduce a team of multiple robots and develop a sensor fusion model using the signal strength ratio from the paired robots in centralized and decentralized manners. We have implemented and validated the algorithms under a hardware-driven simulation and physical experiments

Modeling the Energy Performance of Event-Driven Wireless Sensor Network by Using Static Sink and Mobile Sink

Wireless Sensor Networks (WSNs) designed for mission-critical applications suffer from limited sensing capacities, particularly fast energy depletion. Regarding this, mobile sinks can be used to balance the energy consumption in WSNs, but the frequent location updates of the mobile sinks can lead to data collisions and rapid energy consumption for some specific sensors. This paper explores an optimal barrier coverage based sensor deployment for event driven WSNs where a dual-sink model was designed to evaluate the energy performance of not only static sensors, but Static Sink (SS) and Mobile Sinks (MSs) simultaneously, based on parameters such as sensor transmission range r and the velocity of the mobile sink v, etc. Moreover, a MS mobility model was developed to enable SS and MSs to effectively collaborate, while achieving spatiotemporal energy performance efficiency by using the knowledge of the cumulative density function (cdf), Poisson process and M/G/1 queue. The simulation results verified that the improved energy performance of the whole network was demonstrated clearly and our eDSA algorithm is more efficient than the static-sink model, reducing energy consumption approximately in half. Moreover, we demonstrate that our results are robust to realistic sensing models and also validate the correctness of our results through extensive simulations

Vehicle path verification using wireless sensor networks

Path Verification is a problem where a verifier would like to determine how closely a vehicle actually traversed a path that it claims to have traversed. This problem has critical significances in terms of vehicle mobility. Mobile nodes can be patrols officers or cab drivers, while respective verifiers can be police dispatchers or cab operators. In this paper, we design a sensor network assisted technique for vehicle path verification. In our design, a number of static wireless sensors placed in road segments will serve as witnesses and certify vehicles as they move. Post movement, these witness certificates will be utilized by the verifier to derive the actual path of a suspect vehicle. The challenge now is how to compare a Claimed Path as reported by the vehicle and the Actual Path derived from witness certificates. In this paper, we design a simple, yet effective technique for comparing similarity between two vehicle paths. Our technique extends from Continuous Dynamic Time Warping, which involves constructing a universal manifold from the two paths and then finding the geodesic on the resulting polygonal surface (shortest path along the surface) which is a diagonal from the origin of the surface to the terminal point. This distance is analogous to the Fréchet distance and yields a good measure of the similarity between two paths. Using simulations and real experiments, we demonstrate the performance of our technique from the perspective of detecting false paths claims from correct ones. We also design light-weight cryptographic techniques to prevent vehicle masquerading and certificate forging attacks. A proof of concept experiment was conducted on the streets of Rolla, Missouri. A sensor grid was established on a small section of Rolla and a vehicle with a transmitter was driven through the grid many times. The analysis of the data yielded results consistent with the expected ones --Abstract, page iii

Communication Aware Mobile Robot Teams

The type of scenarios that could benefit from a team of robots that are able to self configure into an ad-hoc multi-hop mobile communication network while completing a task in an unknown environment, range from search and rescue in a partially collapsed building to providing a security perimeter around a region of interest. In this thesis, we present a hybrid system that enables a team of robots to maintain a prescribed end-to-end data rate while moving through a complex unknown environment, in a distributed manner, to complete a specific task. This is achieved by a systematic decomposition of the real-time situational awareness problem into subproblems that can be efficiently solved by distributed optimization. The validity of this approach is demonstrated through multiple simulations and experiments in which the a team of robots is able to accurately map an unknown environment and then transition to complete a traditional situational awareness task. We also present MCTP, a lightweight communication protocol that is specifically designed for use in ad-hoc multi-hop wireless networks composed of low-cost low-power transceivers. This protocol leverages the spatial diversity found in mobile robot teams as well as recently developed robust routing systems designed to minimize the variance of the end-to-end communication link. The combination of the hybrid system and MCTP results in a system that is able to complete a task, with minimal global coordination, while providing near loss-less communication over an ad-hoc multi-hop network created by the members of the team in unknown environments

Transmission Line Fault Monitoring and Identification System by Using Internet of Things

The fault location detection has been a goal of power system engineers, since the creation of distribution and transmission systems. Quick fault detection can help protect the equipment by allowing the disconnection of faulted lines before any significant damage of the equipment. The accurate fault location can help utility personnel remove persistent of the faults and locate the areas where the faults regularly occur, thus reducing the occurrence of fault and minimize the time of power outages. As a result, while the fault location detection schemes have been developed in the past, a variety of algorithms continue to be developed to perform this task more accurately and more effectively. The detection and location of faults on power transmission lines is essential to the protection and maintenance of a power system. Most methods of fault detection and location relate to the measurements of electrical quantities provided by current and voltage transformers. These transformers can be expensive and require physical contact with the monitored high voltage equipment