Supporting Cyber-Physical Systems with Wireless Sensor Networks: An Outlook of Software and Services

Sensing, communication, computation and control technologies are the essential building blocks of a cyber-physical system (CPS). Wireless sensor networks (WSNs) are a way to support CPS as they provide fine-grained spatial-temporal sensing, communication and computation at a low premium of cost and power. In this article, we explore the fundamental concepts guiding the design and implementation of WSNs. We report the latest developments in WSN software and services for meeting existing requirements and newer demands; particularly in the areas of: operating system, simulator and emulator, programming abstraction, virtualization, IP-based communication and security, time and location, and network monitoring and management. We also reflect on the ongoing efforts in providing dependable assurances for WSN-driven CPS. Finally, we report on its applicability with a case-study on smart buildings

A Cyber-Physical Systems Approach to Water Distribution System Monitoring

Water Distribution Systems (WDS) are critical infrastructures of national importance that supply water of desired quality and quantity to consumers. They are prone to damages and attacks such as leaks, breaks, and chemical contamination. Monitoring of WDS for prompt response to such events is of paramount importance. WDS monitoring has been typically performed using static sensors that are strategically placed. These solutions are costly and imprecise. Recently mobile sensors for WDS monitoring has attracted research interest to overcome the shortcomings of static sensors. However, most existing solutions are unrealistic, or disrupt the normal functioning of a WDS. They are also designed to be deployed on-demand, i.e., when the utility manager receives complaints or suspects the presence of a threat. We propose to solve the problem of WDS monitoring through a Cyber-Physical system (CPS) approach. We envision a Cyber-Physical Water Distribution System (CPWDS) with mobile sensors that are deployed in the CPWDS and move with the flow of water in pipes; mobile sensors communicate with static beacons placed outside the pipes and report sensed data; the flows in the pipes are controlled to ensure that the sensors continuously cover the main pipes of the WDS. We propose algorithms to efficiently monitor the WDS with limited number of devices, protocols to efficiently communicate among the devices, and mechanisms to control the flows in the WDS such that consumer demands are met while sensors continuously move around. We evaluate our algorithms, protocols, and design of communication, computation and control components of the CPWDS through a simulator developed specifically to model the movement of sensors through the pipes of the WDS. Our simulations indicate that investing on improving the sensing range of mobile sensors reduces the cost of monitoring significantly. Additionally, the placement of beacons, and the communication range impact the accuracy of localization and estimation of sensor locations. Our flow control system is observed to converge and improve the coverage over time

Safety Risk Management of LEED Building Construction : A BIM based Approach

Green buildings have been gaining popularity in the construction industry due to their low impact on the environment. Green buildings are aimed at creating energy-efficient, healthy, and environment-friendly buildings. However, OSHA records show that about 48% more accidents occur in green building construction as compared to traditional construction methods. Compromising the workers\u27 health and safety questions the true sustainability of the building. Green buildings have been a popular strategy in institutional sustainability agendas. Globally, LEED is the most popular green buildings rating system. Statistics show that an increasing number of construction projects intend to obtain the LEED certification in the next decade. However, elevated worker health and safety risks have been gradually becoming a concern while pursuing LEED credits. However, there exists a limited study comparing the safety hazards occurring in conventional construction practices and green construction practices.This research explores the major safety risks associated with LEED-certified building construction. Failure Mode Effect, Analysis (FMEA) is used to determine the safety risk associated with each LEED credit. LEED credits were ranked based on safety performance. Safety score and incremental cost of LEED credits were used to identify the optimal credit combination for LEED gold certification that reduces the safety risk and minimizes the cost. Bayesian Belief Networks (BBN) was used to analyze the impact of project factors on safety risk. This analysis identified how the risk level of LEED credits changes based on project parameters. Safety risks identified from FMEA and BBN were used to develop Building Information Modelling (BIM)-based solutions to improve worker safety. The outcomes of this research will address the challenges of LEED construction and inform the construction industry in enhancing the health and safety of construction workers with state-of-the-art technolog