Low-cost Sensor Networks Research Articles

Temperature gradient sensor from pulsed power supply duty cycle in ultra‐low‐power energy harvesting system

Directly interfacing sensors that link sensors to micro-controllers without a signal conditioning circuit or an analogue-to-digital converter on the one side and energy harvesting systems on the other side are two key enabling technologies to create self-powered autonomous low-cost and low-maintenance sensor networks. In this reported work, both technologies are concurrently combined in such a way that the duty cycle of the pulsed power supply provided by the harvesting system itself yields in turn a temperature gradient sensor functionality. Originally conceived to power a low-power satellite beacon in a CubeSat project, it has found application, among other applications, in automatic air conditioning and heating systems aiming smart buildings.

A Unique Solution for Designing Low-Cost, Heterogeneous Sensor Networks Using a Middleware Integration Platform

Proprietary sensor network systems are typically expensive, rigid and difficult to incorporate technologies from other vendors. When using competing and incompatible technologies, a non-proprietary system is complex to create because it requires significant technical expertise and effort, which can be more expensive than a proprietary product. This paper presents the Sensor Abstraction Layer (SAL) that provides middleware architectures with a consistent and uniform view of heterogeneous sensor networks, regardless of the technologies involved. SAL abstracts and hides the hardware disparities and specificities related to accessing, controlling, probing and piloting heterogeneous sensors. SAL is a single software library containing a stable hardware-independent interface with consistent access and control functions to remotely manage the network. The end-user has near-real-time access to the collected data via the network, which results in a cost-effective, flexible and simplified system suitable for novice users. SAL has been used for successfully implementing several low-cost sensor network systems.

Development of PMMA-based gas sensor and its evaluation using a VOC dilution flow system

We have developed and evaluated a PMMA-based gas sensor to realize a low-cost sensor network system for monitoring VOCs (volatile organic compounds). The PMMA-based gas sensor consists of a PMMA (poly methyl methacrylate) cantilever, a piezoelectric film of PVDF (polyvinylidene fluoride), and a thin film of PBD (polybutadiene). We began by investigating the influence of PBD coating of a dynamic property of the PMMA cantilever in a higher order resonance mode under atmospheric pressure at room temperature. The PBD-coated PMMA cantilever had a resonant frequency of 341kHz and quality factor of 71 at the 4th flexural vibration mode. Next, we examined the change of resonance frequency in the presence of toluene vapor by setting up a gas sensor evaluation system equipped with a VOC dilution flow system, temperature-controlled chamber, oscillation circuit, and frequency counter. The resonant frequency shifted when the PMMA-based gas sensor was exposed to toluene vapor. The measured toluene sensitivity in the experiment was 0.02Hz/ppm.

A Cost-effective Wireless Sensor Network System for Indoor Air Quality Monitoring Applications

Indoor air pollution has become a serious issue affecting public health. An indoor air quality monitoring system helps in the detection and improvement of indoor air quality. The monitoring systems presently available are very expensive. In this paper, we present a low-cost indoor air quality monitoring wireless sensor network system developed using Arduino, XBee modules, and micro gas sensors. The system that we have developed is capable of collecting six air quality parameters from different locations simultaneously. We have also developed a linear least square estimation-based method for sensor calibration and measurement data conversion. The performance and usefulness of the system are demonstrated by comparing measurement results of our system and a professional-grade air quality measurement device.

Joint Node Localization and Time-Varying Clock Synchronization in Wireless Sensor Networks

The problems of node localization and clock synchronization in wireless sensor networks are naturally tied from a statistical signal processing perspective. In this work, we consider the joint estimation of an unknown node's location and clock parameters by incorporating the effect of imperfections in node oscillators, which render a time varying nature to the clock parameters. The data exchange mechanism is based on a two-way message exchange with anchor nodes. In order to alleviate the computational complexity associated with the optimal maximum a-posteriori estimator, two iterative approaches are proposed as simpler alternatives. The first approach utilizes an Expectation-Maximization (EM) based algorithm which iteratively estimates the clock parameters and the location of the unknown node. The EM algorithm is further simplified by a non-linear processing of the data to obtain a closed form solution of the location estimation problem using least squares (LS). The performance of the estimation algorithms is benchmarked by deriving the Hybrid Cramer-Rao lower bound (HCRB) on the mean square error (MSE) of the estimators. The theoretical findings are corroborated by simulation studies which reveal that the LS estimator closely matches the performance of the EM algorithm for small time of arrival measurement noise, and is well suited for implementation in low cost sensor networks.

Convergence of MANET and WSN in IoT Urban Scenarios

Ubiquitous smart environments, equipped with low-cost and easy-deployable wireless sensor networks (WSNs) and widespread mobile ad hoc networks (MANETs), are opening brand new opportunities in wide-scale urban monitoring. Indeed, MANET and WSN convergence paves the way for the development of brand new Internet of Things (IoT) communication platforms with a high potential for a wide range of applications in different domains. Urban data collection, i.e., the harvesting of monitoring data sensed by a large number of collaborating sensors, is a challenging task because of many open technical issues, from typical WSN limitations (bandwidth, energy, delivery time, etc.) to the lack of widespread WSN data collection standards, needed for practical deployment in existing and upcoming IoT scenarios. In particular, effective collection is crucial for classes of smart city services that require a timely delivery of urgent data such as environmental monitoring, homeland security, and city surveillance. After surveying the existing WSN interoperability efforts for urban sensing, this paper proposes an original solution to integrate and opportunistically exploit MANET overlays, impromptu, and collaboratively formed over WSNs, to boost urban data harvesting in IoT. Overlays are used to dynamically differentiate and fasten the delivery of urgent sensed data over low-latency MANET paths by integrating with latest emergent standards/specifications for WSN data collection. The reported experimental results show the feasibility and effectiveness (e.g., limited coordination overhead) of the proposed solution.

A Survey on Wireless Sensor Networks Architectural Model, Topology, Service and Security

Recent advancement and grown up technologies has enabled the development and implementation of low-cost, energy efficient and versatile sensor networks. Sensor networks are built up with sensors that have the ability to sense fiscal or environmental property. Assumption can be made that Wireless Sensing Network (WSN) is able to sense environmental conditions at Nano and gaseous level. In this paper, first the system architecture of WSN is described. The network may maintain several architectural protocol and topologies. WSN provides some services which are maintained by layered architecture. Another important issue regarding wireless networking is the security challenges. This work guided to a concept of several security issues and discussion to overcome the challenging issues.

Lightweight Location Verification Algorithms for Wireless Sensor Networks

The knowledge of sensors' locations is crucial information for many applications in Wireless Sensor Networks (WSNs). When sensor nodes are deployed in hostile environments, the localization schemes are vulnerable to various attacks, e.g., wormhole attack, pollution attack, range enlargement/reduction attack, and etc. Therefore, sensors' locations are not trustworthy and need to be verified before they can be used by location-based applications. Previous verification schemes either require group-based deployment knowledge of the sensor field, or depend on expensive or dedicated hardware, thus they cannot be used for low-cost sensor networks. In this paper, we propose a lightweight location verification system that performs both “on-spot” and “in-region” location verifications. The on-spot verification intends to verify whether the locations claimed by sensors are far from their true spots beyond a certain distance. We propose two algorithms that detect abnormal locations by exploring the inconsistencies between sensors' claimed locations and their neighborhood observations. The in-region verification verifies whether a sensor is inside an application-specific verification region. Compared to on-spot verification, the in-region verification is tolerable to large errors as long as the locations of sensors don't cause the application to malfunction. We study how to derive the verification region for different applications and design a probabilistic algorithm to compute in-region confidence for each sensor. Experiment results show that our on-spot and in-region algorithms can verify sensors' locations with high detection rate and low false positive rate. They are robust in the presence of malicious attacks that are launched during the verification process. Moreover, compared with previous verification schemes, our algorithms are effective and lightweight because they do not rely on the knowledge of deployment of sensors, and they don't require expensive or dedicated hardware, so our algorithms can be used in any low-cost sensor networks.

Programmable low-power wireless sensors network for vibration monitoring and analysis

Wireless sensors networks have been widely applied for monitoring and structural analysis in the last years. In this work, a low cost, energy saving, high speed and programmable wireless sensors network has been introduced. Each sensor can be programmed individually to perform level measurement at regular intervals, data streaming at programmable sampling rate or event detector. The high speed capability of the proposed wireless nodes inline with its power minimisation efficiency permits their application not only in structural analysis tasks which require intermediate sampling rates, but also in diagnostic analysis which require high sampling rate. The nodes can quickly and easily be installed to any machinery or structure in order to construct a powerful vibration monitoring and analysis system, whether it is permanent or portable for further analysis and diagnosis. The accuracy and efficiency of the proposed system were investigated by several experimental tests.

A Survey on Wireless Sensor Networks Architectural Model, Topology, Service and Security

Recent advancement and grown up technologies has enabled the development and implementation of low-cost, energy efficient and versatile sensor networks. Sensor networks are built up with sensors that have the ability to sense fiscal or environmental property. Assumption can be made that Wireless Sensing Network (WSN) is able to sense environmental conditions at Nano and gaseous level. In this paper, first the system architecture of WSN is described. The network may maintain several architectural protocol and topologies. WSN provides some services which are maintained by layered architecture. Another important issue regarding wireless networking is the security challenges. This work guided to a concept of several security issues and discussion to overcome the challenging issues.

Low-Cost WSN Monitoring and Location of Small Ruminants Using Transmission-Loss Inversion on Open Grassland in Brazil

The practical engineering plausibility of transmission-loss inversion methods using low-cost sensor network technologies for location and tracking of small ruminants is investigated experimentally. Transmission loss is measured in representative outdoor environments using IEEE 802.15.4 technology. The simplest possible propagation model is shown to reflect the general features of the measured propagation data. Its absolute accuracy, however, is probably inadequate for use in a location algorithm based on model inversion without optimization of its parameters. Model calibration to reflect inter-site variation of the propagation environment is suggested as a possible way of realizing a location system with useful accuracy and adequate portability.

A hybrid method of CSMA/CA and TDMA for real-time data aggregation in wireless sensor networks

We study the real-time data aggregation in contention-based wireless sensor networks that use CSMA/CA MAC layer protocols as defined in IEEE 802.15.4 or IEEE 802.11 standard. The problem is, for a given data aggregation tree and a delay bound, to maximize the average transmission success probability of all sensor nodes within the delay bound. In CSMA/CA protocols, the success probability and the expected transmission delay are highly sensitive to node interference, while the node interference is often very high in the large scale sensor networks. We propose a hybrid method that combines the CSMA/CA protocol with TDMA scheduling of transmissions. We divide the child nodes of a parent into groups and schedule the groups into different “time-frames” for transmission. Within the group, the nodes still use the CSMA/CA protocol to compete for data transmission. By doing so, we divide a large collision domain (i.e., all child nodes competing to transmit to their parent) into several small collision domains (i.e., a group of nodes competing for transmission), and the success probability can thus be significantly improved. On the other hand, the “time-frame” used in our method is much larger than the timeslot used in pure TDMA protocols. It only requires loose synchronization of clocks, which is suitable for low-cost sensor networks. We transform our objective of maximizing the average success probability into minimizing the average node interference. We then convert our problem to the maximum weight k-cut problem, which is NP-hard. We propose two efficient heuristic algorithms to solve the problem. Simulation results have shown that our proposed method can improve the success probability significantly.

A Neural Network Approach to Smarter Sensor Networks for Water Quality Monitoring

Environmental monitoring is evolving towards large-scale and low-cost sensor networks operating reliability and autonomously over extended periods of time. Sophisticated analytical instrumentation such as chemo-bio sensors present inherent limitations because of the number of samples that they can take. In order to maximize their deployment lifetime, we propose the coordination of multiple heterogeneous information sources. We use rainfall radar images and information from a water depth sensor as input to a neural network (NN) to dictate the sampling frequency of a phosphate analyzer at the River Lee in Cork, Ireland. This approach shows varied performance for different times of the year but overall produces output that is very satisfactory for the application context in question. Our study demonstrates that even with limited training data, a system for controlling the sampling rate of the nutrient sensor can be set up and can improve the efficiency of the more sophisticated nodes of the sensor network.

Internet-Enabled Wireless Structural Monitoring Systems: Development and Permanent Deployment at the New Carquinez Suspension Bridge

AbstractDense networks of low-cost wireless sensors have the potential to facilitate prolific data collection in large and complex infrastructure at costs lower than those historically associated w...

A Biased Extended Kalman Filter for Indoor Localization of a Mobile Agent using Low-Cost IMU and UWB Wireless Sensor Network

Indoor localization of mobile agents using wireless technologies is becoming very important in military and civil applications. This paper introduces an approach for the indoor localization of a mobile agent based on Ultra-WideBand technology using a Biased Extended Kalman Filter (EKF) as a possible technique to improve the localization. The proposed approach allows to use a low-cost IMU (inertial measurement unit) which performances are improved by a calibration procedure. The obtained results show that the filter allows to obtain better result in terms of localization due to the estimation of bias and scale factor.

Integration of RFID and Web Service for Assisted Living

The number of people over 65 years old throughout most stable and prosperous countries in the world is increasing. Availability of their care in their own homes is imperative because of the economic reasons and their choices where to live (World Health Organization, Definition of an older or elderly person. http://www.who.int/healthinfo/survey/ageingdefnolder/en/ ; EQUIP-European Framework for Qualifications in Home Care Services for Older People, http://www.equip-project.com ; Salonen, 2009). "Recent advancement in wireless communications and electronics has enabled the development of low-cost sensor networks. The sensor networks can be utilized in various application areas." (Akyildiz, et al. 2002) These two statements show that there is a great promise in wireless technology and utilizing it in assisted living might be very beneficial to the elderly people. In this paper, we propose software architecture called Location Windows Service (LWS) which integrates the Radio Frequency Identification (RFID) technology and the web service to build an assisted living system for elderly people at home. This architecture monitors the location of elderly people without interfering in their daily activities. Location information messages that are generated as the elderly move from room to room indicate that the elderly person is fit and healthy and going about their normal life. The communication must be timely enough to follow elderly people as they move from room to room without missing a location. Unacknowledged publishing, subscription filtering and short location change messages are also included in this software model to reduce the network traffic in large homes. We propose some defense schemes being applied to the network environment of the assisted living system to prevent any external attacks.

Secure localization with attack detection in wireless sensor networks

Rapid technological advances have enabled the development of low-cost sensor networks for various monitoring tasks, where it is important to estimate the positions of a number of regular sensor nodes whose locations cannot be known apriori. We address the problem of localizing the regular nodes with range-based location references obtained from certain anchor nodes referred to as beacons, particularly in an adverse environment where some of the beacons may be compromised. We propose an innovative modular solution featuring two lightweight modules that are for dedicated functionalities, respectively, but can also be closely integrated. First, we harness simple geometric triangular rules and an efficient voting technique to enable the attack detection module, which identifies and filters out malicious location references. We then develop a secure localization module that computes and clusters certain reference points, and the position of the concerned regular node is estimated with the centroid of the most valuable reference points identified. Extensive simulations show that our attack detection module can detect compromised beacons effectively, and the secure localization module can subsequently provide a dependable localization service in terms of bounded estimation error. The integrated system turns out to be tolerant of malicious attacks even in highly challenging scenarios.

OMG U got flu? Analysis of shared health messages for bio-surveillance

BackgroundMicro-blogging services such as Twitter offer the potential to crowdsource epidemics in real-time. However, Twitter posts (‘tweets’) are often ambiguous and reactive to media trends. In order to ground user messages in epidemic response we focused on tracking reports of self-protective behaviour such as avoiding public gatherings or increased sanitation as the basis for further risk analysis.ResultsWe created guidelines for tagging self protective behaviour based on Jones and Salathé (2009)’s behaviour response survey. Applying the guidelines to a corpus of 5283 Twitter messages related to influenza like illness showed a high level of inter-annotator agreement (kappa 0.86). We employed supervised learning using unigrams, bigrams and regular expressions as features with two supervised classifiers (SVM and Naive Bayes) to classify tweets into 4 self-reported protective behaviour categories plus a self-reported diagnosis. In addition to classification performance we report moderately strong Spearman’s Rho correlation by comparing classifier output against WHO/NREVSS laboratory data for A(H1N1) in the USA during the 2009-2010 influenza season.ConclusionsThe study adds to evidence supporting a high degree of correlation between pre-diagnostic social media signals and diagnostic influenza case data, pointing the way towards low cost sensor networks. We believe that the signals we have modelled may be applicable to a wide range of diseases.

Optimized Energy Cluster Routing for Energy Balanced Consumption inLow-cost Sensor Network

Energy balanced consumption routing is based on assumption that the nodes consume energy both in transmitting and receiving. Lopsided energy consumption is an intrinsic problem in low-cost sensor networks characterized by multihop routing and in many traffic overhead pattern networks, and this irregular energy dissipation can significantly reduce network lifetime. In this paper, we study the problem of maximizing network lifetime through balancing energy consumption for uniformly deployed low-cost sensor networks. We formulate the energy consumption balancing problem as an optimal balancing data transmitting problem by combining the ideas of corona cluster based network division and optimized transmitting state routing strategy together with data transmission. We propose a localized cluster based routing scheme that guarantees balanced energy consumption among clusters within each corona. We develop a new energy cluster based routing protocol called “OECR”. We design an offline centralized algorithm with time complexity O (log n) (n is the number of clusters) to solve the transmitting data distribution problem aimed at energy balancing consumption among nodes in different cluster. An approach for computing the optimal number of clusters to maximize the network lifetime is also presented. Based on the mathematical model, an optimized energy cluster routing (OECR) is designed and the solution for extending OEDR to low-cost sensor networks is also presented. Simulation results demonstrate that the proposed routing scheme significantly outperforms conventional energy routing schemes in terms of network lifetime.

Review on Protocol based Approaches to Extend Lifetime of Wireless Sensor Networks

Researchers in wireless Micro-sensor networks (M-WSN) have proposed various protocols for energy conservations. Each protocol is aimed to optimize power utilization in wireless sensor networks. The different protocol approaches optimize power consumption either considering their application areas or network topologies. This paper studies various energy-saving protocols for micro sensor networks and presents their brief classifications. An M-WSN is a group of hundreds or thousands of small energy-limited sensors that are densely deployed in a large geographical region. These micro sensors in sensor network are autonomous devices responsible for forwarding locally collected data to a central node called sink node by following multi-hop wireless paths. The sink node performs data fusion to form a single meaningful result. The micro sensors work by utilizing limited battery-power, the considerable part is to use this power for a maximum time. Although recent developments in electronics has enabled the development of low-cost & low-power sensors networks, still there is a challenging job of energy conservation optimization within the wireless sensor networks (WSNs).