Real-Time Wireless Sensor-Actuator Networks for Cyber-Physical Systems

A cyber-physical system (CPS) employs tight integration of, and coordination between computational, networking, and physical elements. Wireless sensor-actuator networks provide a new communication technology for a broad range of CPS applications such as process control, smart manufacturing, and data center management. Sensing and control in these systems need to meet stringent real-time performance requirements on communication latency in challenging environments. There have been limited results on real-time scheduling theory for wireless sensor-actuator networks. Real-time transmission scheduling and analysis for wireless sensor-actuator networks requires new methodologies to deal with unique characteristics of wireless communication. Furthermore, the performance of a wireless control involves intricate interactions between real-time communication and control. This thesis research tackles these challenges and make a series of contributions to the theory and system for wireless CPS. (1) We establish a new real-time scheduling theory for wireless sensor-actuator networks. (2) We develop a scheduling-control co-design approach for holistic optimization of control performance in a wireless control system. (3) We design and implement a wireless sensor-actuator network for CPS in data center power management. (4) We expand our research to develop scheduling algorithms and analyses for real-time parallel computing to support computation-intensive CPS

Automated building monitoring using a wireless sensor network

Building monitoring is one of the challenging issues in building construction, due to its high cost and the time consuming procedure for implementation and maintenance. It is also a critical issue that directly affects building security, safety, and management, energy saving, and tenants' convenience. Wireless sensor networking is a new networking technology that holds great promise for monitoring, evaluation and management of buildings. However, sufficient work has not been done in the application part of wireless sensor networks for building monitoring. In this thesis, we show how advanced wireless sensor technology can be used by building managers to monitor climate conditions, brightness level, lamp status and room occupancy in buildings as well as by the wireless sensor network administrator to monitor the nodes' connectivity and conditions in the network. We conceive of the building monitoring application as being divided into three main parts. First, wireless sensor hardware is programmed to process signals from sensors and transmit the data in a suitable format to a gateway/server application using multi-hop routing. The second task involves the forwarding of the signals sent by the wireless sensor nodes to the end user application by the gateway/server further retrieval and analysis. The third part consists of an end user application for processing the sensor data sent by the wireless sensor nodes and then forwarded by the gateway/server. The end user application visualizes the network topology, network connectivity graph and real time information of individual motes. In addition, this application provides the real time analysis of the data and functionalities for search and observation. Finally, the end user application allows users to analyze the rooms and network conditions by mining the database using different parameters such as the type of data and the time of data acquisition. The system and related analysis were applied on a real case study -- the eighth and ninth floors of the Engineering and Visual Arts building of Concordia University

SMART TRANSPORTATION SYSTEMS: IOT-CONNECTED WIRELESS SENSOR NETWORKS FOR TRAFFIC CONGESTION MANAGEMENT

Smart Transportation Systems (STS) are crucial to alleviating urban traffic congestion. This paper examines how gridlock managers might use IoT-related remote sensor networks to improve transportation productivity and flexibility. The study's initial inquiry examines traffic congestion's negative consequences on cities, including increased travel time, fuel consumption, and pollution. It emphasizes the need for creative solutions to reduce traffic and improve urban life. The solution's IoT-enabled wireless sensor networks simplify real-time data collection and analysis. A dense sensor network at important traffic sites can collect significant data on traffic flow, vehicle density, and road conditions. This data enables smart traffic management methods and better transportation systems. Sensor hubs, information transmission standards, and information analysis methodologies are examined in the exploratory article. It discusses network-sending challenges such as power productivity, flexibility, and information security and proposes solutions. The essay also considers synergies with autonomous cars, smart traffic signal systems, and IoT-connected wireless sensor networks in transportation infrastructure. These pairings boost gridlock executives' viability and STS's future. An IoT-associated remote sensor network was dispatched to a metropolitan region in the exploration piece to test the proposed configuration. The research examines the data, how traffic management tactics were applied, and how traffic flow, trip time, and environmental sustainability improved. This research shows that IoT-connected wireless sensor networks may transform smart transportation system traffic congestion management. Advanced analytics and real-time data may help cities reduce congestion, increase mobility, and develop sustainable cities

BIM and sensor-based data management system for construction safety monitoring

Purpose This research aims to investigate the integration of real-time monitoring of thermal conditions within confined work environments through wireless sensor network (WSN) technology when integrated with building information modelling (BIM). A prototype system entitled confined space monitoring system (CoSMoS), which provides an opportunity to incorporate sensor data for improved visualization through new add-ins to BIM software, was then developed. Design/methodology/approach An empirical study was undertaken to compare and contrast between the performances (over a time series) of various database models to find a back-end database storage configuration that best suits the needs of CoSMoS. Findings Fusing BIM data with information streams derived from wireless sensors challenges traditional approaches to data management. These challenges encountered in the prototype system are reported upon and include issues such as hardware/software selection and optimization. Consequently, various database models are explored and tested to find a database storage that best suits the specific needs of this BIM-wireless sensor technology integration. Originality value This work represents the first tranche of research that seeks to deliver a fully integrated and advanced digital built environment solution for automating the management of health and safety issues on construction sites. </jats:sec

Performance assessment of real-time data management on wireless sensor networks

Technological advances in recent years have allowed the maturity of Wireless Sensor Networks (WSNs), which aim at performing environmental monitoring and data collection. This sort of network is composed of hundreds, thousands or probably even millions of tiny smart computers known as wireless sensor nodes, which may be battery powered, equipped with sensors, a radio transceiver, a Central Processing Unit (CPU) and some memory. However due to the small size and the requirements of low-cost nodes, these sensor node resources such as processing power, storage and especially energy are very limited. Once the sensors perform their measurements from the environment, the problem of data storing and querying arises. In fact, the sensors have restricted storage capacity and the on-going interaction between sensors and environment results huge amounts of data. Techniques for data storage and query in WSN can be based on either external storage or local storage. The external storage, called warehousing approach, is a centralized system on which the data gathered by the sensors are periodically sent to a central database server where user queries are processed. The local storage, in the other hand called distributed approach, exploits the capabilities of sensors calculation and the sensors act as local databases. The data is stored in a central database server and in the devices themselves, enabling one to query both. The WSNs are used in a wide variety of applications, which may perform certain operations on collected sensor data. However, for certain applications, such as real-time applications, the sensor data must closely reflect the current state of the targeted environment. However, the environment changes constantly and the data is collected in discreet moments of time. As such, the collected data has a temporal validity, and as time advances, it becomes less accurate, until it does not reflect the state of the environment any longer. Thus, these applications must query and analyze the data in a bounded time in order to make decisions and to react efficiently, such as industrial automation, aviation, sensors network, and so on. In this context, the design of efficient real-time data management solutions is necessary to deal with both time constraints and energy consumption. This thesis studies the real-time data management techniques for WSNs. It particularly it focuses on the study of the challenges in handling real-time data storage and query for WSNs and on the efficient real-time data management solutions for WSNs. First, the main specifications of real-time data management are identified and the available real-time data management solutions for WSNs in the literature are presented. Secondly, in order to provide an energy-efficient real-time data management solution, the techniques used to manage data and queries in WSNs based on the distributed paradigm are deeply studied. In fact, many research works argue that the distributed approach is the most energy-efficient way of managing data and queries in WSNs, instead of performing the warehousing. In addition, this approach can provide quasi real-time query processing because the most current data will be retrieved from the network. Thirdly, based on these two studies and considering the complexity of developing, testing, and debugging this kind of complex system, a model for a simulation framework of the real-time databases management on WSN that uses a distributed approach and its implementation are proposed. This will help to explore various solutions of real-time database techniques on WSNs before deployment for economizing money and time. Moreover, one may improve the proposed model by adding the simulation of protocols or place part of this simulator on another available simulator. For validating the model, a case study considering real-time constraints as well as energy constraints is discussed. Fourth, a new architecture that combines statistical modeling techniques with the distributed approach and a query processing algorithm to optimize the real-time user query processing are proposed. This combination allows performing a query processing algorithm based on admission control that uses the error tolerance and the probabilistic confidence interval as admission parameters. The experiments based on real world data sets as well as synthetic data sets demonstrate that the proposed solution optimizes the real-time query processing to save more energy while meeting low latency.Fundação para a Ciência e Tecnologi

A Cloud Based Disaster Management System

The combination of wireless sensor networks (WSNs) and 3D virtual environments opens a new paradigm for their use in natural disaster management applications. It is important to have a realistic virtual environment based on datasets received from WSNs to prepare a backup rescue scenario with an acceptable response time. This paper describes a complete cloud-based system that collects data from wireless sensor nodes deployed in real environments and then builds a 3D environment in near real-time to reflect the incident detected by sensors (fire, gas leaking, etc.). The system’s purpose is to be used as a training environment for a rescue team to develop various rescue plans before they are applied in real emergency situations. The proposed cloud architecture combines 3D data streaming and sensor data collection to build an efficient network infrastructure that meets the strict network latency requirements for 3D mobile disaster applications. As compared to other existing systems, the proposed system is truly complete. First, it collects data from sensor nodes and then transfers it using an enhanced Routing Protocol for Low-Power and Lossy Networks (RLP). A 3D modular visualizer with a dynamic game engine was also developed in the cloud for near-real time 3D rendering. This is an advantage for highly-complex rendering algorithms and less powerful devices. An Extensible Markup Language (XML) atomic action concept was used to inject 3D scene modifications into the game engine without stopping or restarting the engine. Finally, a multi-objective multiple traveling salesman problem (AHP-MTSP) algorithm is proposed to generate an efficient rescue plan by assigning robots and multiple unmanned aerial vehicles to disaster target locations, while minimizing a set of predefined objectives that depend on the situation. The results demonstrate that immediate feedback obtained from the reconstructed 3D environment can help to investigate what–if scenarios, allowing for the preparation of effective rescue plans with an appropriate management effort.info:eu-repo/semantics/publishedVersio

Total Water Management System

The purpose of this pilot project is to embark on a total water management system (TWMS) that enables the efficient and effective management of water by addressing both quantity and quality aspects through real time water quality monitoring, water usage monitoring and water leakage monitoring in water distribution network. TWMS is a previous project embarked on by Universiti Teknologi PERONAS (UTP) research community, which is a wireless sensor network (WSN) testbed set up in one of the research laboratories in UTP. In this project, the major work shall focus on implementing a wireless solution in UTP students' villages, to provide a WSN data collection for monitoring and analysis purposes hence the objective is to find an optimal water management solution. The targeted monitoring and control setup would be the wash rooms located at the selected levels and selected houses of each male and female village. Wireless sensors that are installed on the strategic water pipes will be used to measure the water usage, water leakage, and water quality. All data collected would be transmitted automatically to a lab server for storage, archive, and analysis. Command and control signaling can be transmitted wirelessly to control the possible leakages. The outcome of this project shall provide vital statistics and information on the managing and control of water losses, which ultimately may contribute to the improvement of the sustainability of clean water supply and distribution. Moreover this project might provide a platform for wireless sensor technology to become a strategic enabler for a total water management syste

Towards Real-time Wireless Sensor Networks

Wireless sensor networks are poised to change the way computer systems interact with the physical world. We plan on entrusting sensor systems to collect medical data from patients, monitor the safety of our infrastructure, and control manufacturing processes in our factories. To date, the focus of the sensor network community has been on developing best-effort services. This approach is insufficient for many applications since it does not enable developers to determine if a system\u27s requirements in terms of communication latency, bandwidth utilization, reliability, or energy consumption are met. The focus of this thesis is to develop real-time network support for such critical applications. The first part of the thesis focuses on developing a power management solution for the radio subsystem which addresses both the problem of idle-listening and power control. In contrast to traditional power management solutions which focus solely on reducing energy consumption, the distinguishing feature of our approach is that it achieves both energy efficiency and real-time communication. A solution to the idle-listening problem is proposed in Energy Efficient Sleep Scheduling based on Application Semantics: ESSAT). The novelty of ESSAT lies in that it takes advantage of the common features of data collection applications to determine when to turn on and off a node\u27s radio without affecting real-time performance. A solution to the power control problem is proposed in Real-time Power Aware-Routing: RPAR). RPAR tunes the transmission power for each packet based on its deadline such that energy is saved without missing packet deadlines. The main theoretical contribution of this thesis is the development of novel transmission scheduling techniques optimized for data collection applications. This work bridges the gap between wireless sensor networks and real-time scheduling theory, which have traditionally been applied to processor scheduling. The proposed approach has significant advantages over existing design methodologies:: 1) it provides predictable performance allowing for the performance of a system to be estimated upon its deployment,: 2) it is possible to detect and handle overload conditions through simple rate control mechanisms, and: 3) it easily accommodates workload changes. I developed this framework under a realistic interference model by coordinating the activities at the MAC, link, and routing layers. The last component of this thesis focuses on the development of a real-time patient monitoring system for general hospital units. The system is designed to facilitate the detection of clinical deterioration, which is a key factor in saving lives and reducing healthcare costs. Since patients in general hospital wards are often ambulatory, a key challenge is to achieve high reliability even in the presence of mobility. To support patient mobility, I developed the Dynamic Relay Association Protocol -- a simple and effective mechanism for dynamically discovering the right relays for forwarding patient data -- and a Radio Mapping Tool -- a practical tool for ensuring network coverage in 802.15.4 networks. We show that it is feasible to use low-power and low-cost wireless sensor networks for clinical monitoring through an in-depth clinical study. The study was performed in a step-down cardiac care unit at Barnes-Jewish Hospital. This is the first long-term study of such a patient monitoring system

Modeling and Predicting Future Trajectories of Moving Objects in a Constrained Network

http://ieeexplore.ieee.org/Advances in wireless sensor networks and positioning technologies enable traffic management (e.g. routing traffic) that uses real-time data monitored by GPS-enabled cars. Location management has become an enabling technology in such application. The location modeling and trajectory prediction of moving objects are the fundamental components of location management in mobile locationaware applications. In this paper, we model the road network and moving objects in a graph of cellular automata (GCA), which makes full use of the constraints of the network and the stochastic behavior of the traffic. A simulation-based method based on graphs of cellular automata is proposed to predict future trajectories. Our technique strongly differs from the linear prediction method, which has low prediction accuracy and requires frequent updates when applied to real traffic with velocity changes. The experiments, carried on two different datasets, show that the simulation-based prediction method provides higher accuracy than the linear prediction method