Sudden Event Monitoring of Civil Infrastructure Using Demand-Based Wireless Smart Sensors

Wireless smart sensors (WSS) have been proposed as an effective means to reduce the high cost of wired structural health monitoring systems. However, many damage scenarios for civil infrastructure involve sudden events, such as strong earthquakes, which can result in damage or even failure in a matter of seconds. Wireless monitoring systems typically employ duty cycling to reduce power consumption; hence, they will miss such events if they are in power-saving sleep mode when the events occur. This paper develops a demand-based WSS to meet the requirements of sudden event monitoring with minimal power budget and low response latency, without sacrificing high-fidelity measurements or risking a loss of critical information. In the proposed WSS, a programmable event-based switch is implemented utilizing a low-power trigger accelerometer; the switch is integrated in a high-fidelity sensor platform. Particularly, the approach can rapidly turn on the WSS upon the occurrence of a sudden event and seamlessly transition from low-power acceleration measurement to high-fidelity data acquisition. The capabilities of the proposed WSS are validated through laboratory and field experiments. The results show that the proposed approach is able to capture the occurrence of sudden events and provide high-fidelity data for structural condition assessment in an efficient manner

Smart Energy Management for Smart Grids

This book is a contribution from the authors, to share solutions for a better and sustainable power grid. Renewable energy, smart grid security and smart energy management are the main topics discussed in this book

Adaptive tracking of people and vehicles using mobile platforms

Tracking algorithms have important applications in detection of humans and vehicles for border security and other areas. For large-scale deployment of such algorithms, it is critical to provide methods for their cost- and energy-efficient realization. To this end, commodity mobile devices have significant potential for use as prototyping and testing platforms due to their low cost, widespread availability, and integration of advanced communications, sensing, and processing features. Prototypes developed on mobile platforms can be tested, fine-tuned, and demonstrated in the field and then provide reference implementations for application-specific disposable sensor node implementations that are targeted for deployment. In this paper, we develop a novel, adaptive tracking system that is optimized for energy-efficient, real-time operation on off-the-shelf mobile platforms. Our tracking system applies principles of dynamic data-driven application systems (DDDAS) to periodically monitor system operating characteristics and apply these measurements to dynamically adapt the specific classifier configurations that the system employs. Our resulting adaptive approach enables powerful optimization of trade-offs among energy consumption, real-time performance, and tracking accuracy based on time-varying changes in operational characteristics. Through experiments employing an Android-based tablet platform, we demonstrate the efficiency of our proposed tracking system design for multimode detection of human and vehicle targets.publishedVersionPeer reviewe

Microgrids

Microgrids are a growing segment of the energy industry, representing a paradigm shift from centralized structures toward more localized, autonomous, dynamic, and bi-directional energy networks, especially in cities and communities. The ability to isolate from the larger grid makes microgrids resilient, while their capability of forming scalable energy clusters permits the delivery of services that make the grid more sustainable and competitive. Through an optimal design and management process, microgrids could also provide efficient, low-cost, clean energy and help to improve the operation and stability of regional energy systems. This book covers these promising and dynamic areas of research and development and gathers contributions on different aspects of microgrids in an aim to impart higher degrees of sustainability and resilience to energy systems

Energy efficient data collection and dissemination protocols in self-organised wireless sensor networks

Wireless sensor networks (WSNs) are used for event detection and data collection in a plethora of environmental monitoring applications. However a critical factor limits the extension of WSNs into new application areas: energy constraints. This thesis develops self-organising energy efficient data collection and dissemination protocols in order to support WSNs in event detection and data collection and thus extend the use of sensor-based networks to many new application areas. Firstly, a Dual Prediction and Probabilistic Scheduler (DPPS) is developed. DPPS uses a Dual Prediction Scheme combining compression and load balancing techniques in order to manage sensor usage more efficiently. DPPS was tested and evaluated through computer simulations and empirical experiments. Results showed that DPPS reduces energy consumption in WSNs by up to 35% while simultaneously maintaining data quality and satisfying a user specified accuracy constraint. Secondly, an Adaptive Detection-driven Ad hoc Medium Access Control (ADAMAC) protocol is developed. ADAMAC limits the Data Forwarding Interruption problem which causes increased end-to-end delay and energy consumption in multi-hop sensor networks. ADAMAC uses early warning alarms to dynamically adapt the sensing intervals and communication periods of a sensor according to the likelihood of any new events occurring. Results demonstrated that compared to previous protocols such as SMAC, ADAMAC dramatically reduces end-to-end delay while still limiting energy consumption during data collection and dissemination. The protocols developed in this thesis, DPPS and ADAMAC, effectively alleviate the energy constraints associated with WSNs and will support the extension of sensorbased networks to many more application areas than had hitherto been readily possible

A Practical Review to Support the Implementation of Smart Solutions within Neighbourhood Building Stock

The construction industry has witnessed an increase in the use of digital tools and smart solutions, particularly in the realm of building energy automation. While realising the potential benefits of smart cities, a broader scope of smart initiatives is required to support the transition from smart buildings towards smart neighbourhoods, which are considered critical urban development units. To support the interplay of smart solutions between buildings and neighbourhoods, this study aimed to collect and review all the smart solutions presented in existing scientific articles, the technical literature, and realised European projects. These solutions were classified into two main sections, buildings and neighbourhoods, which were investigated through five domains: building-energy-related uses, renewable energy sources, water, waste, and open space management. The quantitative outcomes demonstrated the potential benefits of implementing smart solutions in areas ranging from buildings to neighbourhoods. Moreover, this research concluded that the true enhancement of energy conservation goes beyond the building’s energy components and can be genuinely achieved by integrating intelligent neighbourhood elements owing to their strong interdependencies. Future research should assess the effectiveness of these solutions in resource conservation