Distributed Sensing

We present the use of swept wavelength interferometry for distributed fiber-optic, temperature measurements of up to 850degC over a 1m fiber segment in commercially available, single mode, gold coated fiber. The interrogation technique is based on measuring the spectral shift of the intrinsic Rayleigh backscatter signal along the optical fiber and converting the spectral shift to temperature.

Featured Application: Distributed fibre optic sensors for geo-hydrological applications: a comprehensive review about methodology, weaknesses, and strengths. Abstract: Distributed optical fibre sensing, employing either Rayleigh, Raman, or Brillouin scattering, is the only physical-contact sensor technology capable of accurately estimating physical fields with spatial continuity along the fibre. This unique feature and the other features of standard optical fibre sensors (e.g., minimal invasiveness and lightweight, remote powering/interrogating capabilities) have for many years promoted the technology to be a promising candidate for geo-hydrological monitoring. Relentless research efforts are being undertaken to bring the technology to complete maturity through laboratory, physical models, and in-situ tests. The application of distributed optical fibre sensors to geo-hydrological monitoring is here reviewed and discussed, along with basic principles and main acquisition techniques. Among the many existing geo-hydrological processes, the emphasis is placed on those related to soil levees, slopes/landslide, and ground subsidence that constitute a significant percentage of current geohazards.

This paper presents the design, implementation, and operation of a novel distributed fault-tolerant middleware. It uses interconnected WSNs that implement the Map-Reduce paradigm, consisting of several low-cost and low-power mini-computers (Raspberry Pi). Specifically, we explain the steps for the development of a novice, fault-tolerant Map-Reduce algorithm which achieves high system availability, focusing on network connectivity. Finally, we showcase the use of the proposed system based on simulated data for crowd monitoring in a real case scenario, i.e. a historical building in Greece (M. Hatzidakis’ residence). The technical novelty of this article lies in presenting a viable low-cost and low-power solution for crowd sensing without using complex and resource-intensive AI structures or image/video recognition techniques.

A wireless sensor network (WSN) consists of spatially distributed autonomous sensors that cooperatively
monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion,
or pollutants, at different locations. Recent advances in low-power highly-integrated electronics,
advances in micro-electro-mechanical systems (MEMS), rapid growth in the type and quality of available
sensors, and progress in communication have allowed WSNs to achieve an unprecedented growth in
commercial, industrial and military applications. In order to better understand WSNs, we look at their
network architectures. In this survey, we classify existing WSN architectures into specific groups based
on WSN behaviour and data flow characteristics. Existing architectures are described and presented
along with their advantages and disadvantages. The existing architectures are also evaluated in terms of
most common WSN performance parameters such as network lifetime, latency, reliability, quality of
service (QoS), fidelity, scalability, modularity, and ease of deployment.

Sensor networks offer a powerful combination of distributed sensing, computing and communication. They lend themselves to countless applications and, at the same time, offer numerous challenges due to their peculiarities, primarily the stringent energy constraints to which sensing nodes are typically subjected. The distinguishing traits of sensor networks have a direct impact on the hardware design of the nodes at at least four levels: power source, processor, communication hardware, and sensors. Various hardware platforms have already been designed to test the many ideas spawned by the research community and to implement applications to virtually all fields of science and technology. We are convinced that CAS will be able to provide a substantial contribution to the development of this exciting field.

– A distributed sensing/fusion network consists of more than one (spatially) separated sensors, each with possibly different characteristics and not all of them sensing the same en-vironment. Due to their vast applicability, there has been a flurry of recent activity in the ...

Electronic noses are intelligent instruments that are able to classify and quantify different gas/odours. Here we suggest the integration of a small form factor computer inside the electronic nose. This concept allows us to easily provide remote connectivity, large data storage and complex signal processing. The evolution of this technology will permit distributed sensing with applications to agriculture and environment. Proposed instrument allows incoming connections for remote control of bad odours in landfill sites. Preliminary approach to this application using commercial sensors and mixture model pattern recognition scheme is exposed.

– A short range wireless network platform, based on Bluetooth technology and on a Round Robin scheduling is presented. The objective is to build an application independent platform, to support a distributed sensing and actuation control system, which will be used in an Unmanned Aerial Vehicle (UAV). This platform provides the advantages of wireless communications while assuring low weight, small energy consumption and reliable communications.

Due to limited energy of sensor nodes in a wireless sensor network, an energy-efficient routing protocol with static clustering and dynamic structure (ERP-SCDS) is proposed in this paper. Utilizing virtual points in a corona-based wireless sensor network, static clusters with dynamic structures are formed in ERP-SCDS. Moreover, next-round cluster heads are selected in advance to avoid a deadlock when the old cluster heads die. Finally, a simple relay node selection mechanism instead of a complicated multi-hop route discovery algorithm is further designed for ERP-SCDS. Integrating these mechanisms enables ERP-SCDS to form balanced cluster sizes to prolong the network lifetime. Via simulations, we demonstrate that ERP-SCDS significantly outperforms LEACH, HEED, and Hausdorff previously proposed in the literature.

Wireless Sensor and Actuator Networks (WSANs) combine sensors and actuators interconnected by wireless networks in order to perform distributed sensing and acting tasks. Closed-loop controllers can therefore be deployed on WSANs; such systems have to meet specific requirements in terms of performance, dependability, energy and cost which raises great challenges due to the unreliability of wireless communications. A way to ensure that a system meets the required properties is to model it and go through its analysis. Building a model requires both deep knowledge on the system as well as on the used framework. Therefore there is a need for frameworks well-suited to the targeted systems and to the properties to verify. We propose an approach meeting these conditions and a simulation framework, Samovar, based on Matlab / Simulink, allowing the modeling of the network protocols (Mac and routing services) and the resources sharing policy thanks to the TrueTime toolbox. Several classes of c...

We study the adjointness problem for the closed extensions of a general b-elliptic operator A in x^{-\nu}Diff^m_b(M;E), \nu>0, initially defined as an unbounded operator A:C_c^\infty(M;E)\subset x^\mu L^2_b(M;E)\to x^\mu L^2_b(M;E), \mu \in \R. The case where A is a symmetric semibounded operator is of particular interest, and we give a complete description of the domain of the Friedrichs extension of such an operator.

This paper presents the design, implementation, and operation of a novel distributed fault-tolerant middleware. It uses interconnected WSNs that implement the Map-Reduce paradigm, consisting of several low-cost and low-power mini-computers (Raspberry Pi). Specifically, we explain the steps for the development of a novice, fault-tolerant Map-Reduce algorithm which achieves high system availability, focusing on network connectivity. Finally, we showcase the use of the proposed system based on simulated data for crowd monitoring in a real case scenario, i.e. a historical building in Greece (M. Hatzidakis’ residence). The technical novelty of this article lies in presenting a viable low-cost and low-power solution for crowd sensing without using complex and resource-intensive AI structures or image/video recognition techniques.

This paper outlines a project involving the development of an FMS in the Manufacturing Engineering Technology Department at the Rochester Institute of Technology (USA). This project is currently in progress and is expected to be completed by May 1998. The most interesting aspect of this project is that it is being done as part of an undergraduate capstone course called process design and a graduate course on FMS. The cell will be implemented using smart distributed system (SDS) from Honeywell Micro Switch. In this system, the various sensors and actuators communicate with the central control computer using field bus technology. This is state-of-the-art technology in computer based data acquisition and control. The hardware and software aspects of the FMS are being developed by a group of fifteen undergraduate students and one graduate student, under the guidance of the author and technical experts from Honeywell Micro Switch. The FMS will consist of two identical milling centers and...

A short range wireless network platform, based on Bluetooth technology and on a Round Robin scheduling is presented. The objective is to build an application independent platform, to support a distributed sensing and actuation control system, which will be used in an Unmanned Aerial Vehicle (UAV). This platform provides the advantages of wireless communications while assuring low weight, small energy consumption and reliable communications.

Wireless Sensor Networks (WSNs) are emerging as powerful platforms for distributed embedded computing supporting a variety of high-impact applications. However programming WSN applications is a complex task which requires suitable paradigms and technologies capable of supporting the specific characteristics of such networks which uniquely integrate distributed sensing, computation and communication. Mobile agents are a distributed computing paradigm based on code

Body Sensor Networks (BSNs) represent an emerging technology which has received much attention recently due to its enormous potential to enable remote, real-time, continuous and non-invasive monitoring of people in health-care, entertainment, fitness, sport, social interaction. Signal processing for BSNs usually comprises of multiple levels of data abstraction, from raw sensor data to data calculated from processing steps such as feature extraction and classification. This paper presents a multi-layer task model based on the concept of Virtual Sensors to improve architecture modularity and design reusability. Virtual Sensors are abstractions of components of BSN systems that include sensor sampling and processing tasks and provide data upon external requests. The Virtual Sensor model implementation relies on SPINE2, an open source domain-specific framework that is designed to support distributed sensing operations and signal processing for wireless sensor networks and enables code reusability, efficiency, and application interoperability. The proposed model is applied in the context of gait analysis through wearable sensors. A gait analysis system is developed according to a SPINE2-based Virtual Sensor architecture and experimentally evaluated. Obtained results confirm that great effectiveness can be achieved in designing and implementing BSN applications through the Virtual Sensor approach while maintaining high efficiency and accuracy.