Energy Efficient Cooperation in Underlay RFID Cognitive Networks for a Water Smart Home

Shrinking water  resources all over the world and increasing  costs of water consumption  have prompted  water users  and distribution companies  to come up with water conserving strategies. We have proposed an energy-efficient  smart water monitoring application in [1], using low power RFIDs. In the home environment,  there exist many primary interferences within a room, such as cell-phones,  Bluetooth  devices, TV signals, cordless phones and WiFi devices.  In order to reduce the interference  from our proposed RFID network for these primary  devices, we have proposed a cooperating  underlay  RFID cognitive network for our smart application on water.  These underlay  RFIDs should strictly adhere to the interference thresholds to work in parallel with the primary wireless devices [2].  This work is an extension of our previous  ventures proposed in [2,3], and we enhanced the previous efforts by introducing  a new system model and RFIDs.  Our proposed scheme is mutually energy efficient and maximizes the signal-to-noise ratio (SNR) for the RFID link, while keeping the interference levels for the primary  network below a certain threshold. A closed form expression for the probability density function (pdf) of the SNR at the destination reader/writer and outage probability are derived. Analytical results are verified through simulations. It is also shown that in comparison to non-cognitive selective cooperation,  this scheme performs  better in the low SNR region for cognitive networks. Moreover, the hidden Markov model’s (HMM) multi-level variant hierarchical hidden Markov model (HHMM) approach is used for pattern recognition and event detection for the data received for this system [4]. Using this model, a feedback and decision algorithm is also developed.  This approach has been applied  to simulated water pressure data from RFID motes, which were embedded in metallic water pipes

Framework for integrated oil pipeline monitoring and incident mitigation systems

Wireless Sensor Nodes (motes) have witnessed rapid development in the last two decades. Though the design considerations for Wireless Sensor Networks (WSNs) have been widely discussed in the literature, limited investigation has been done for their application in pipeline surveillance. Given the increasing number of pipeline incidents across the globe, there is an urgent need for innovative and effective solutions for deterring the incessant pipeline incidents and attacks. WSN pose as a suitable candidate for such solutions, since they can be used to measure, detect and provide actionable information on pipeline physical characteristics such as temperature, pressure, video, oil and gas motion and environmental parameters. This paper presents specifications of motes for pipeline surveillance based on integrated systems architecture. The proposed architecture utilizes a Multi-Agent System (MAS) for the realization of an Integrated Oil Pipeline Monitoring and Incident Mitigation System (IOPMIMS) that can effectively monitor and provide actionable information for pipelines. The requirements and components of motes, different threats to pipelines and ways of detecting such threats presented in this paper will enable better deployment of pipeline surveillance systems for incident mitigation. It was identified that the shortcomings of the existing wireless sensor nodes as regards their application to pipeline surveillance are not effective for surveillance systems. The resulting specifications provide a framework for designing a cost-effective system, cognizant of the design considerations for wireless sensor motes used in pipeline surveillance

IoT-enabled water distribution systems - a comparative technological review

Water distribution systems are one of the critical infrastructures and major assets of the water utility in a nation. The infrastructure of the distribution systems consists of resources, treatment plants, reservoirs, distribution lines, and consumers. A sustainable water distribution network management has to take care of accessibility, quality, quantity, and reliability of water. As water is becoming a depleting resource for the coming decades, the regulation and accounting of the water in terms of the above four parameters is a critical task. There have been many efforts towards the establishment of a monitoring and controlling framework, capable of automating various stages of the water distribution processes. The current trending technologies such as Information and Communication Technologies (ICT), Internet of Things (IoT), and Artificial Intelligence (AI) have the potential to track this spatially varying network to collect, process, and analyze the water distribution network attributes and events. In this work, we investigate the role and scope of the IoT technologies in different stages of the water distribution systems. Our survey covers the state-of-the-art monitoring and control systems for the water distribution networks, and the status of IoT architectures for water distribution networks. We explore the existing water distribution systems, providing the necessary background information on the current status. This work also presents an IoT Architecture for Intelligent Water Networks - IoTA4IWNet, for real-time monitoring and control of water distribution networks. We believe that to build a robust water distribution network, these components need to be designed and implemented effectively

From MANET to people-centric networking: Milestones and open research challenges

In this paper, we discuss the state of the art of (mobile) multi-hop ad hoc networking with the aim to present the current status of the research activities and identify the consolidated research areas, with limited research opportunities, and the hot and emerging research areas for which further research is required. We start by briefly discussing the MANET paradigm, and why the research on MANET protocols is now a cold research topic. Then we analyze the active research areas. Specifically, after discussing the wireless-network technologies, we analyze four successful ad hoc networking paradigms, mesh networks, opportunistic networks, vehicular networks, and sensor networks that emerged from the MANET world. We also present an emerging research direction in the multi-hop ad hoc networking field: people centric networking, triggered by the increasing penetration of the smartphones in everyday life, which is generating a people-centric revolution in computing and communications

A Simulation Platform for Evaluating RFID and WSN’s Energy Efficiencies

Advances in the wireless, RFID and sensor technologies has given rise to a plethora of diverse WSN motes that can be used in association with numerous applications. Experimenting with new MAC algorithms and various functionalities on a real sensor network to obtain energy efficiency is both time consuming and expensive especially when these different mote platforms are deployed in one application. Generally Simulators are used to approximate the performance of MAC protocols. Out of the numerous simulators available, none can simulate the energy efficiencies given different types of motes and environments in one application. Hence, the need of a simulation platform for a mix deployment of different types of WSNs and RFIDs is felt to access application performance requirements while curtailing energy consumption to enhance application lifetime. In this paper, we presents an extension of our effort EnergySim [1], which is a simulation platform developed dedicatedly for evaluating energy efficiencies. In this paper we have discussed the simulation modes, methodology and architecture of our proposed simulator with some future extensions presented at the end of the paper

Cyber–Physical–Social Frameworks for Urban Big Data Systems: A Survey

The integration of things’ data on the Web and Web linking for things’ description and discovery is leading the way towards smart Cyber–Physical Systems (CPS). The data generated in CPS represents observations gathered by sensor devices about the ambient environment that can be manipulated by computational processes of the cyber world. Alongside this, the growing use of social networks offers near real-time citizen sensing capabilities as a complementary information source. The resulting Cyber–Physical–Social System (CPSS) can help to understand the real world and provide proactive services to users. The nature of CPSS data brings new requirements and challenges to different stages of data manipulation, including identification of data sources, processing and fusion of different types and scales of data. To gain an understanding of the existing methods and techniques which can be useful for a data-oriented CPSS implementation, this paper presents a survey of the existing research and commercial solutions. We define a conceptual framework for a data-oriented CPSS and detail the various solutions for building human–machine intelligence

Spectral Clustering And Support Vector Classification For Localizing Leakages In Water Distribution Networks – The ICeWater Project Approach

This paper presents a framework based on hydraulic simulation and machine learning for supporting Water Distribution Network (WDN) managers in localizing leakages, while reducing time and costs for investigation, intervention and rehabilitation. As a first step, hydraulic simulation is used to run different leakage scenarios by introducing a leak on each pipe, in turn, and varying its severity. As output of each scenario run, pressure and flow variations in correspondence of the actual monitoring points into the WDN, and with respect to the faultless model, are stored. Scenarios clustering is aimed at grouping together leaks generating similar effects, in terms of observable pressure and flow variations. This analysis is performed by creating a similarity graph, where nodes are scenarios and edges are weighted by the similarity between pairs of scenarios. Spectral clustering, a graph-clustering technique, is here proposed according to its usually higher performances with respect to traditional data-points clustering. Then each scenario is labeled with its cluster by obtaining a labeled dataset on which a Support Vector Machine (SVM) with RBF-kernel is trained. When an actual leak is detected, the variations in measured pressure and flow with respect to the faultless hydraulic model are given as input to the trained SVM which assigns them to a specific cluster, whose corresponding pipes are provided as the hydraulic components to check for leakage. Since spectral clustering induces a non-linear transformation, from Input Space (i.e., pressure and flow variations) to Feature Space (i.e., most relevant eigen-vectors) where clusters are obtained, the SVM encodes the non-linear relationship of pressure and flow variations with the scenarios cluster. The SVM is able to remap efficiently the results from spectral clustering toward the Input Space giving the probably leaky pipes even for pressure and flow variations not included in the simulated leakage scenarios

The Penetration of Internet of Things in Robotics: Towards a Web of Robotic Things

As the Internet of Things (IoT) penetrates different domains and application areas, it has recently entered also the world of robotics. Robotics constitutes a modern and fast-evolving technology, increasingly being used in industrial, commercial and domestic settings. IoT, together with the Web of Things (WoT) could provide many benefits to robotic systems. Some of the benefits of IoT in robotics have been discussed in related work. This paper moves one step further, studying the actual current use of IoT in robotics, through various real-world examples encountered through a bibliographic research. The paper also examines the potential ofWoT, together with robotic systems, investigating which concepts, characteristics, architectures, hardware, software and communication methods of IoT are used in existing robotic systems, which sensors and actions are incorporated in IoT-based robots, as well as in which application areas. Finally, the current application of WoT in robotics is examined and discussed

Cloud Internet of Things for the Smart Environment of a Smart City

The environmental service area for smart city construction provides sustainability, economic, stage, and safe energy savings in building a smart city. The smart environment monitoring system can manage the agricultural environment, water quality, and air quality of smart cities through the Internet of Things and cloud computing technology. Smart environmental monitoring (SEM) systems to reduce environmental problems in smart cities are important service domains that can improve citizens\u27 quality of life. The purpose of this project is to identify services through the introduction of technologies to solve environmental problems in smart cities, the use and management of the technologies introduced. The project findings are: (a) The SEM system collects environmental data through IoT devices and analyzes it through cloud computing. (b) Data from the SEM system is collected through the Internet of Things based on a wireless sensor network. The collected data is transmitted to the cloud computing platform to be analyzed and monitored. (c) For wireless Internet connections between the two technologies can connect through unique services of Message Queuing Telemetry Transport and cloud platform. (d) The SEM applications were analyzed for Smart Agricultural Monitoring, Smart Water Quality Monitoring, and Smart Air Quality Monitoring. (e) The project is analyzed the transmitted data using Amazon Web Service and Google Cloud Platform. When the analyzed environmental parameters deviate from normal values, email notification can be sent to detect abnormalities in environmental parameters. In addition, the connection between IoT devices and cloud platforms can confirm the normal connection of IoT devices to establish a security system by obtaining credibility and reliability for the connection between the two technologies. As a result, the collaboration between IoT and cloud computing technology can show how a smart environment service domain can help smart city citizens