Advancing experimentation-as-a-service through urban IoT experiments

Smart cities are becoming a vibrant application domain for a number of science fields. As such, service providers and stakeholders are beginning to integrate co-creation aspects into current implementations to shape the future smart city solutions. In this context, holistic solutions are required to test such aspects in real city-scale Internet of Things (IoT) deployments, considering the complex city ecosystems. In this paper, we discuss OrganiCity's implementation of an experimentation-as-a-service (EaaS) framework, presenting a toolset that allows developing, deploying, and evaluating smart city solutions in a one-stop shop manner. This is the first time such an integrated toolset is offered in the context of a large-scale IoT infrastructure, which spans across multiple European cities. We discuss the design and implementation of the toolset, presenting our view on what EaaS should provide, and how it is implemented. We present initial feedback from 25 experimenter teams that have utilized this toolset in the OrganiCity project, along with a discussion on two detailed actual use cases to validate our approach. Learnings from all experiments are discussed as well as architectural considerations for platform scaling. Our feedback from experimenters indicates that EaaS is a viable and useful approach.The authors would like to thank the experimenter teams and volunteers who participated in OrganiCit

Real-time Edge Analytics for Cyber Physical Systems using Compression Rates Real-time Edge Analytics for Cyber Physical Systems using Compression Rates

Abstract There is a movement in many practical applications of Cyber-Physical Systems to push processing to the edge. This is particularly important were the CPS is carrying out monitoring and control, where the latency between the decision making and control message reception should be minimal. However, CPS are limited by the capabilities of the typically battery powered low resourced devices. In this paper we present a self-adaptive scheme that both reduces the amount of resources required to store high sample rate data at the edge and at the same time carries out initial data analytics. Using out Smart Water datasets, plus a selection from other real world CPS applications, we show that our algorithm reduces computation by 98%; data volumes by 55%; while requiring only 11KB of memory at runtime (including the compression algorithm). In addition we show that our system supports self-tuning and automatic reconfiguration which means that manual tuning is alleviated and the scheme can be both applied to any kind of raw data automatically and is able self-optimize as the nature of the incoming data changes over time

Next generation cyber-physical water distribution systems

Over the last decade, there has been a trend where water utility companies aim to make water distribution networks more intelligent in order to improve their quality of service, reduce water and energy waste, minimize maintenance costs etc., by incorporating Information and Communications Technologies (ICT). Current state of the art solutions use expensive power hungry deployments to monitor and transmit water network states periodically in order to detect anomalous behaviors, such as water leakage and bursts, and control water network assets. However, more than 97% of water network assets are found in remote areas, away from power and are often in geographically remote underpopulated areas; facts that make current approaches unsuitable for next generation more dynamic adaptive water networks. Battery-driven wireless sensor/actuator-based solutions are theoretically the perfect choice to support next generation cyber-physical water distribution systems. In this context, this thesis answers the question: "How can the communication be optimized to achieve sustainable Cyber-Physical Systems (CPS) deployed in such harsh environments exploiting limited resources by combining Information, Control, and Communication theory (I2C)? " In order to efficiently utilize underground wireless sensor and actuator network infrastructures, the concepts of edge data processing, anomaly detection and localization, based on compression, stream analyses and graph theory, are introduced. Furthermore, energy optimization and network sustainability by exploiting data-rate and communication scheduling adaptation, based on Lyapunov optimization, is proposed; while the benefits of aperiodic communication are investigated by accommodating event-triggered control technique into smart water networks. In addition to simulations based on real data, WaterBox and BentoBox evaluation platforms were developed to evaluate the proposed algorithms and prove the benefits of event-triggered control and Low Power Wide Area (LPWA) communication technologies against the state-of-the-art solutions. Through theoretical analysis, simulations, and real testbed experiments, the proposed algorithms and systems are shown to outperform contemporary solutions by achieving communication and actuation optimization, data reliability enhancement, while ensuring the sustainable operation of smart water networks. The work presented in this thesis should be of interest to researchers in the emerging areas Cyber-Physical Systems (CPS), Internet of Things (IoT), and Information and Communications Technology (ICT) for smart sustainable cites.Open Acces

Communication schemes for centralized and decentralized event-triggered control systems

Energy constraint long-range wireless sensor/actuator-based solutions are theoretically the perfect choice to support the next generation of city-scale cyber-physical systems. Traditional systems adopt periodic control which increases network congestion and actuations while burdens the energy consumption. Recent control theory studies overcome these problems by introducing aperiodic strategies, such as event-triggered control (ETC). In spite of the potential savings, these strategies assume actuator continuous listening, while ignoring the sensing energy costs. In this paper, we fill this gap, by enabling sensing and actuator listening duty cycling and proposing two innovative medium access control protocols for three decentralized ETC approaches. A laboratory experimental test bed, which emulates a smart water network, was modeled and extended to evaluate the impact of system parameters and the performance of each approach. Experimental results reveal the predominance of the decentralized ETC against the classic periodic control either in terms of communication or actuation by promising significant system lifetime extension.Team Tamas Keviczk

Demystifying low-power wide-area communications for city IoT applications

Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICO, Volume 03-07-October-2016, 3 October 2016, Article number 2980162, Pages 2-8Low Power Wide Area (LPWA) communication technologies have the potential to provide a step change in the enablement of cost-effective and energy efficient Internet of Things (IoT) applications. With an increase in the number of offerings available the real performance of these emerging technologies remain unclear. That is, each technology comes with its own advantages and limitations; yet there is a lack of comparative studies that examine their trade-offs based on empirical evidence. This poses a major challenge to IoT solution architects and developers in selecting an appropriate technology for an envisioned IoT application in a given deployment context. In this paper, we look beyond data sheets and white papers of LPWA communication technologies and provide insights into the performance of three emerging LPWA solutions based on real world experiments with different traffic loads and in different urban deployment contexts. Under the context of this study, specialized hardware was created to incorporate the different technologies and provide scientific quantitative and qualitative information related to data rates, success rates, transmission mode energy and power consumption, and communication ranges. The results of experimentation highlight the practicalities of placing LPWA technologies in real spaces and provide guidelines to IoT solution developers in terms of LPWA technology selection. Overall aim is to facilitate the design of new LPWA technologies and adaptive communication strategies that inform future IoT platforms

Enhancing Health Care Delivery through Ambient Intelligence Applications

This paper presents the implementation of a smart environment that employs Ambient Intelligence technologies in order to augment a typical hospital room with smart features that assist both patients and medical staff. In this environment various wireless and wired sensor technologies have been integrated, allowing the patient to control the environment and interact with the hospital facilities, while a clinically oriented interface allows for vital sign monitoring. The developed applications are presented both from a patient’s and a doctor’s perspective, offering different services depending on the user’s role. The results of the evaluation process illustrate the need for such a service, leading to important conclusions about the usefulness and crucial role of AmI in health care