A technological framework for data-driven IoT systems: application on landslide monitoring

The emergence of the paradigm of the Internet of Things has underpinned the development of data-driven cyber-physical systems that collect and process data that is dense both in space and time. The application areas of such data-driven IoT systems are numerous and their socio-economic impact of great importance as they enable the monitoring and management of processes in sectors ranging from urban management to management of the natural environment. In this work, we introduce and detail an end-to-end technological framework for data-driven IoT systems for landslide monitoring. The framework is articulated in three tiers – namely data acquisition, data curation and data presentation. For each tier we present and detail its design and development aspects; from the IoT hardware design and the wireless communication technologies of choice, to how Big Data infrastructure and Machine Learning components can be combined to support a sophisticated presentation tier that delivers the true added value of a system to its final users. The framework is validated, extended and fine-tuned by means of two pilots at locations experiencing the impact of different landslide types and activity. This work qualitatively improves upon existing methods of landslide monitoring and showcases how data-driven IoT systems can pave new pathways for interdisciplinary research as well as generate positive impact on modern societies

Faculty of Engineering and Design. Research Review

STUDENTS AND ACADEMICS - This publication introduces you to the department or school and then each faculty member’s research areas, research applications, and their most recent activities. A comprehensive index can be found at the back of this publication to help guide you by specific areas of interest, as well as point out interdisciplinary topics and researchers. INDUSTRY LEADERS - This publication includes information regarding specific facilities, labs, and research areas of departments and schools as well as individual faculty members and researchers. A comprehensive index can be found at the back of this publication to help guide you by specific areas of interest, as well as point out interdisciplinary topics and researchers

DESIGN OF RELIABLE AND SUSTAINABLE WIRELESS SENSOR NETWORKS: CHALLENGES, PROTOCOLS AND CASE STUDIES

Integrated with the function of sensing, processing, and wireless communication, wireless sensors are attracting strong interest for a variety of monitoring and control applications. Wireless sensor networks (WSNs) have been deployed for industrial and remote monitoring purposes. As energy shortage is a worldwide problem, more attention has been placed on incorporating energy harvesting devices in WSNs. The main objective of this research is to systematically study the design principles and technical approaches to address three key challenges in designing reliable and sustainable WSNs; namely, communication reliability, operation with extremely low and dynamic power sources, and multi-tier network architecture. Mathematical throughput models, sustainable WSN communication strategies, and multi-tier network architecture are studied in this research to address these challenges, leading to protocols for reliable communication, energy-efficient operation, and network planning for specific application requirements. To account for realistic operating conditions, the study has implemented three distinct WSN testbeds: a WSN attached to the high-speed rotating spindle of a turning lathe, a WSN powered by a microbial fuel cell based energy harvesting system, and a WSN with a multi-tier network architecture. With each testbed, models and protocols are extracted, verified and analyzed. Extensive research has studied low power WSNs and energy harvesting capabilities. Despite these efforts, some important questions have not been well understood. This dissertation addresses the following three dimensions of the challenge. First, for reliable communication protocol design, mathematical throughput or energy efficiency estimation models are essential, yet have not been investigated accounting for specific application environment characteristics and requirements. Second, for WSNs with energy harvesting power sources, most current networking protocols do not work efficiently with the systems considered in this dissertation, such as those powered by extremely low and dynamic energy sources. Third, for multi-tier wireless network system design, routing protocols that are adaptive to real-world network conditions have not been studied. This dissertation focuses on these questions and explores experimentally derived mathematical models for designing protocols to meet specific application requirements. The main contributions of this research are 1) for industrial wireless sensor systems with fast-changing but repetitive mobile conditions, understand the performance and optimal choice of reliable wireless sensor data transmission methods, 2) for ultra-low energy harvesting wireless sensor devices, design an energy neutral communication protocol, and 3) for distributed rural wireless sensor systems, understand the efficiency of realistic routing in a multi-tier wireless network. Altogether, knowledge derived from study of the systems, models, and protocols in this work fuels the establishment of a useful framework for designing future WSNs

Monitoring, Modelling and Management of Water Quality

Different types of pressures, such as nutrients, micropollutants, microbes, nanoparticles, microplastics, or antibiotic-resistant genes, endanger the quality of water bodies. Evidence-based pollution control needs to be built on the three basic elements of water governance: Monitoring, modeling, and management. Monitoring sets the empirical basis by providing space- and time-dependent information on substance concentrations and loads, as well as driving boundary conditions for assessing water quality trends, water quality statuses, and providing necessary information for the calibration and validation of models. Modeling needs proper system understanding and helps to derive information for times and locations where no monitoring is done or possible. Possible applications are risk assessments for exceedance of quality standards, assessment of regionalized relevance of sources and pathways of pollution, effectiveness of measures, bundles of measures or policies, and assessment of future developments as scenarios or forecasts. Management relies on this information and translates it in a socioeconomic context into specific plans for implementation. Evaluation of success of management plans again includes well-defined monitoring strategies. This book provides an important overview in this context

Natural and Technological Hazards in Urban Areas

Natural hazard events and technological accidents are separate causes of environmental impacts. Natural hazards are physical phenomena active in geological times, whereas technological hazards result from actions or facilities created by humans. In our time, combined natural and man-made hazards have been induced. Overpopulation and urban development in areas prone to natural hazards increase the impact of natural disasters worldwide. Additionally, urban areas are frequently characterized by intense industrial activity and rapid, poorly planned growth that threatens the environment and degrades the quality of life. Therefore, proper urban planning is crucial to minimize fatalities and reduce the environmental and economic impacts that accompany both natural and technological hazardous events

Geographic Information Systems for Real-Time Environmental Sensing at Multiple Scales

The purpose of this investigation was to design, implement, and apply a real-time geographic information system for data intensive water resource research and management. The research presented is part of an ongoing, interdisciplinary research program supporting the development of the Intelligent River® observation instrument. The objectives of this research were to 1) design and describe software architecture for a streaming environmental sensing information system, 2) implement and evaluate the proposed information system, and 3) apply the information system for monitoring, analysis, and visualization of an urban stormwater improvement project located in the City of Aiken, South Carolina, USA. This research contributes to the fields of software architecture and urban ecohydrology. The first contribution is a formal architectural description of a streaming environmental sensing information system. This research demonstrates the operation of the information system and provides a reference point for future software implementations. Contributions to urban ecohydrology are in three areas. First, a characterization of soil properties for the study region of the City of Aiken, SC is provided. The analysis includes an evaluation of spatial structure for soil hydrologic properties. Findings indicate no detectable structure at the scales explored during the study. The second contribution to ecohydrology comes from a long-term, continuous monitoring program for bioinfiltration basin structures located in the study area. Results include an analysis of soil moisture dynamics based on data collected at multiple depths with high spatial and temporal resolution. A novel metric is introduced to evaluate the long-term performance of bioinfiltration basin structures based on soil moisture observation data. Findings indicate a decrease in basin performance over time for the monitored sites. The third contribution to the field of ecohydrology is the development and application of a spatially and temporally explicit rainfall infiltration and excess model. The model enables the simulation and visualization of bioinfiltration basin hydrologic response at within-catchment scales. The model is validated against observed soil moisture data. Results include visualizations and stormwater volume calculations based on measured versus predicted bioinfiltration basin performance over time

Integrated modeling in urban hydrology: reviewing the role of monitoring technology in overcoming the issue of ‘big data’ requirements

Increasingly, the application of models in urban hydrology has undergone a shift toward integrated structures that recognize the interconnected nature of the urban landscape and both the natural and engineered water cycles. Improvements in computational processing during the past few decades have enabled the application of multiple, connected model structures that link previously disparate systems together, incorporating feedbacks and connections. Many applications of integrated models look to assess the impacts of environmental change on physical dynamics and quality of landscapes. Whilst these integrated structures provide a more robust representation of natural dynamics, they often place considerable data requirements on the user, whereby data are required at contrasting spatial and temporal scales which can often transcend multiple disciplines. Concomitantly, our ability to observe complex, natural phenomena at contrasting scales has improved considerably with the advent of increasingly novel monitoring technologies. This has provided a pathway for reducing model uncertainty and improving our confidence in modeled outputs by implementing suitable monitoring regimes. This commentary assesses how component models of an exemplar integrated model have advanced over the past few decades, with a critical focus on the role of monitoring technologies that have enabled better identification of the key physical process. This reduces the uncertainty of processes at contrasting spatial and temporal scales, through a better characterization of feedbacks which then enhances the utility of integrated model applications

Data monitoring web services in a virtual lab environment

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2002.Includes bibliographical references (p. 88).Environmental issues have become of prime concern due to dramatic increase in the pollution levels in all parts of the world. Underlying aquifer flow in environmentally sensitive places plays an important role in characterizing the environmental condition of the place. There is thus a pressing need for monitoring and real time analysis of hydrological data over areas of environmental interest. Coupling the emerging sensing and wireless technologies with an internet infrastructure can enable efficient data monitoring and real-time analysis of environmental conditions over an area of interest. Information gathered from various data sources regarding the change in water level and quality during various seasons can then be used to characterize trends in the physical, chemical and biological condition of the environment. Efficient real-time monitoring furnished with fast data rendering and decision-making capabilities can go a long way in monitoring Civil and Environmental Engineering infrastructure. The speed and reliability necessary for such a task can be achieved only by using a distributed infrastructure, with dedicated resources to data acquisition, archival and rendering. Distributed development technologies like DCOM, CORBA, RMI and SOAP, essentially extensions of simple RPC protocols, provide the interconnectivity between different components of such a distributed infrastructure. The present work discusses these distributed development technologies and compares them in the context of the Smartwells project.by Ashish Sadashiv Kulkarni.M.Eng

The future of Earth observation in hydrology

In just the past 5 years, the field of Earth observation has progressed beyond the offerings of conventional space-agency-based platforms to include a plethora of sensing opportunities afforded by CubeSats, unmanned aerial vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically of the order of 1 billion dollars per satellite and with concept-to-launch timelines of the order of 2 decades (for new missions). More recently, the proliferation of smart-phones has helped to miniaturize sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Start-up companies that did not exist a decade ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of traditional satellite missions. With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-metre resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via high-altitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the "internet of things" as an entirely new measurement domain. Such global access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparent is that the tools and techniques afforded by this array of novel and game-changing sensing platforms present our community with a unique opportunity to develop new insights that advance fundamental aspects of the hydrological sciences. To accomplish this will require more than just an application of the technology: in some cases, it will demand a radical rethink on how we utilize and exploit these new observing systems

Architecting a Blockchain-Based Framework for the Internet of Things

Traditionally, Internet-of-Things (IoT) solutions are based on centralized infrastructures, which necessitate high-end servers for handling and transferring data. Centralized solutions incur high costs associated to maintaining centralized servers, and do not provide built-in guarantees against security threats and trust issues. Therefore, it is an essential research problem to mitigate the aforementioned problems by developing new methods for IoT decentralisation. In recent years, blockchain technology, the underlying technology of Bitcoin, has attracted research interest as the potential missing link towards building a truly decentralized, trustless and secure environment for the IoT. Nevertheless, employing blockchain in the IoT has significant issues and challenges, related to scalability since all transactions logged in a blockchain undergo a decentralized consensus process. This thesis presents the design and implementation of a blockchain-based decentralized IoT framework that can leverage the inherent security characteristics of blockchains, while addressing the challenges associated with developing such a framework. This decentralized IoT framework aims to employ blockchains in combination with other peer-to-peer mechanisms to provide: access control; secure IoT data transfer; peer-to-peer data-sharing business models; and secure end-to-end IoT communications, without depending upon a centralized intermediary for authentication or data handling. This framework uses a multi-tiered blockchain architecture with a control-plane/data-plane split, in that the bulk data is transferred through peer-to-peer data transfer mechanisms, and blockchains are used to enforce terms and conditions and store relevant timestamped metadata. Implementations of the blockchain-based framework have been presented in a multitude of use-cases, to observe the framework's viability and adaptability in real-world scenarios. These scenarios involved traceability in supply chains, IoT data monetization and security in end-to-end communications.With all the potential applications of the blockchain-based framework within the IoT, this thesis takes a step towards the goal of a truly decentralized IoT