Wireless Sensor Motes Research Articles

Smartdust Network for Tactical Border Surveillance Using Multiple Signatures

The paper aims at designing a system for border surveillance using the concept of smartdust technology. Smartdusts are small dust like wireless sensor motes with multiple on-board sensors and microcontroller. In real time, thousands of such smartdust motes must be deployed in a large area. The motes can form a network among them and has wireless connection to outside world. Onboard hardware include a variety of sensors for vibration/seismic, magnetic, acoustic and thermal signature recognition, a microcontroller for processing these sensor values and a radio transceiver for communication over a wireless network. In this experimental project, we have designed one central monitoring mote and two smartdust motes using ARM controller, IEEE radio transceiver and sensors.The central monitoring mote also displays the tracking history of intrusion on enabling a switch. Keywords:Advanced RISC Machine (ARM), Cortex microcontroller software interface standard (CMSIS), Inter Integrated Circuit (I 2 C), MEMS accelerometer, Serial Peripheral Interface (SPI),Smartdust mote.

Autonomous wireless radar sensor mote for target material classification

Autonomous wireless sensor networks consisting of different types of sensor modalities have been receiving greater attention from researchers due to their versatility and portability. These autonomous sensor networks commonly include passive sensors such as infrared, acoustic, vibration, and magnetic nodes. However, fusion of active sensors in the integrated sensor network, such as Doppler radars, may offer powerful capabilities for many different sensing and classification tasks. In this work, we demonstrate the design and implementation of an autonomous wireless sensor network integrating a Doppler sensor with commercial off-the-shelf components. We investigate the effect of various types of target materials on the measured radar signal as one of the applications of the newly designed radar–mote network. Different types of materials affect the amount of energy reflected back to the source of an electromagnetic wave. We obtain mathematical and simulation models for the reflectivity of different homogeneous non-conducting materials and study the effect of such reflectivity on the classification of targets. We validate our simulation results using real experimental data collected through our autonomous radar–mote sensor network using various types of targets.

Healthcare System through Wireless Body Area Networks (WBAN) using Telosb Motes

Due to the increased demand for an effective communication technology in the health care sector, a wireless network is needed that effectively monitors the patient’s vital sign and send reports concurrently to the remote system. This increases the comfort level of monitoring the patients continuously. The main idea of this article work is to build up a WBAN that endlessly monitors human healthiness parameters and reports information to the nearby PC/sinks. The small wearable devices which is memory efficient, energy efficient, less computational complexity are deployed on the patient to be monitored. They self-configure to endlessly monitor critical signs such as heart beat, core temperature etc. The energy efficiency and transmission delay is analyzed by using Cooja simulator. Finally the design is implemented in the Telosb wireless sensor motes.

Rethinking Java call stack design for tiny embedded devices

The ability of tiny embedded devices to run large feature-rich programs is typically constrained by the amount of memory installed on such devices. Furthermore, the useful operation of these devices in wireless sensor applications is limited by their battery life. This paper presents a call stack redesign targeted at an efficient use of RAM storage and CPU cycles by a Java program running on a wireless sensor mote. Without compromising the application programs, our call stack redesign saves 30% of RAM, on average, evaluated over a large number of benchmarks. On the same set of bench-marks, our design also avoids frequent RAM allocations and deallocations, resulting in average 80% fewer memory operations and 23% faster program execution. These may be critical improvements for tiny embedded devices that are equipped with small amount of RAM and limited battery life. However, our call stack redesign is equally effective for any complex multi-threaded object oriented program developed for desktop computers. We describe the redesign, measure its performance and report the resulting savings in RAM and execution time for a wide variety of programs.

Secure Initialization of Multiple Constrained Wireless Devices for an Unaided User

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REAL TIME WIRELESS AIR POLLUTION MONITORING SYSTEM

Air pollution has significant influence on the concentration of constituents in the atmosphere leading to effects like global warming and acid rains. To avoid such adverse imbalances in the nature, an air pollution monitoring system is utmost important. This paper attempts to develop an effective solution for pollution monitoring using wireless sensor networks (WSN) on a real time basis namely real time wireless air pollution monitoring system. Commercially available discrete gas sensors for sensing concentration of gases l ike CO 2 , NO 2, CO and O 2 are calibrated using appropriate calibration technologies. These pre - calibrated gas sensors are then integrated with the wireless sensor motes for field deployment at the campus and the Hyderabad city using multi hop data aggregatio n algorithm. A light weight middleware and a web interface to view the live pollution data in the form of numbers and charts from the test beds was developed and made available from anywhere on the internet. Other parameters like temperature and humidity w ere also sensed along with gas concentrations to enable data analysis through data fusion techniques. Experimentation carried out using the developed wireless air pollution monitoring system under different physical conditions show that the system collects reliable source of real time fine - grain pollution data.

Distributed iterative quantization for interference characterization in wireless networks

We consider the problem of estimating the distance to a device transmitting in the 2.4 GHz ISM band that is interfering with users of an 802.11b wireless network. Accurate estimation of this quantity enables the wireless network to dynamically change its operating characteristics, such as its transmit power levels and channel assignments, to minimize this interference. The estimate is made by a cluster of wireless sensor motes deployed along the edge of an 802.11b network. The motes perform a 1-bit quantization of the Received Signal Strength (RSS) using a dithered quantization framework. The quantized bits are transmitted over a Binary Symmetric Channel (BSC) to the Cluster Head (CH), which then uses a Maximum-Likelihood Estimation (MLE) technique to estimate the unknown parameter. We propose a framework in which the CH uses an iterative parameter estimation scheme in which it provides low-overhead feedback to the motes to adjust their threshold values for the 1-bit dithered quantization process. Evaluation of the Root Mean Squared Error (RMSE) of this iterative scheme shows that it performs significantly better than iterative approaches in which all the motes use either identical thresholds or the non-identical thresholds proposed in Ribeiro and Giannakis (2006) [5] , [19] . Our iterative scheme also tracks sudden changes in the distance to the interferer and is robust to fluctuations in the crossover probability in the BSC.

Low-complexity algorithms for event detection in wireless sensor networks

To ensure that a multi-hop cluster of batterypowered, wireless sensor motes can complete all of its tasks, each task must minimize its use of communication and processing resources. For event detection tasks that are subject to both measurement errors by sensors and communication errors in the wireless channel, this implies that: (i) the Cluster-Head (CH) must optimally fuse the decisions received from its cluster in order to reduce the effect of measurement errors; (ii) the CH and all motes that relay other motes' decisions must adopt lowcomplexity processing and coding algorithms that minimize the effects of communication errors. This paper combines a Maximum a Posteriori (MAP) approach for local and global decisions in multi-hop sensor networks with low-complexity repetition codes and processing algorithms. It is shown by analysis and confirmed by simulation that there exists an odd integer M and an integer KM such the decision error probability at the CH is reduced when: (1) nodes in rings k ≤ KM hops from the CH directly relay their decisions to the CH; (2) nodes in rings k > KM locally fuse groups of M decisions and then use a repetition code to forward these fused decisions to the CH; and (3) KM is a nondecreasing function of M. This algorithm - and hybrid, hierarchical, and compression approaches based on it - enable tradeoffs amongst the probability of error, energy usage, compression ratio, complexity, and time to decision.

Testing ZigBee Motes for Monitoring Refrigerated Vegetable Transportation under Real Conditions

Quality control and monitoring of perishable goods during transportation and delivery services is an increasing concern for producers, suppliers, transport decision makers and consumers. The major challenge is to ensure a continuous ‘cold chain’ from producer to consumer in order to guaranty prime condition of goods. In this framework, the suitability of ZigBee protocol for monitoring refrigerated transportation has been proposed by several authors. However, up to date there was not any experimental work performed under real conditions. Thus, the main objective of our experiment was to test wireless sensor motes based in the ZigBee/IEEE 802.15.4 protocol during a real shipment. The experiment was conducted in a refrigerated truck traveling through two countries (Spain and France) which means a journey of 1,051 kilometers. The paper illustrates the great potential of this type of motes, providing information about several parameters such as temperature, relative humidity, door openings and truck stops. Psychrometric charts have also been developed for improving the knowledge about water loss and condensation on the product during shipments.

Quality of Trilateration: Confidence-Based Iterative Localization

The proliferation of wireless and mobile devices has fostered the demand for context-aware applications, in which location is one of the most significant contexts. Multilateration, as a basic building block of localization, however, has not yet overcome the challenges of 1) poor ranging measurements; 2) dynamic and noisy environments; and 3) fluctuations in wireless communications. Hence, multilateration-based approaches often suffer from poor accuracy and can hardly be employed in practical applications. In this study, we propose Quality of Trilateration (QoT) that quantifies the geometric relationship of objects and ranging noises. Based on QoT, we design a confidence-based iterative localization scheme, in which nodes dynamically select trilaterations with the highest quality for location computation. To validate this design, a prototype network based on wireless sensor motes is deployed and the results show that QoT well represents trilateration accuracy, and the proposed scheme significantly improves localization accuracy.

Adaptive critics for dynamic optimization

A novel action-dependent adaptive critic design (ACD) is developed for dynamic optimization. The proposed combination of a particle swarm optimization-based actor and a neural network critic is demonstrated through dynamic sleep scheduling of wireless sensor motes for wildlife monitoring. The objective of the sleep scheduler is to dynamically adapt the sleep duration to node's battery capacity and movement pattern of animals in its environment in order to obtain snapshots of the animal on its trajectory uniformly. Simulation results show that the sleep time of the node determined by the actor critic yields superior quality of sensory data acquisition and enhanced node longevity.

Experiments With Sensor Motes and Java-DSP

Distributed wireless sensor networks (WSNs) are being proposed for various applications including defense, security, and smart stages. The introduction of hardware wireless sensors in a signal processing education setting can serve as a paradigm for data acquisition, collaborative signal processing, or simply as a platform for obtaining, processing, and analyzing real-life real-time data. In this paper, a software interface that enables the Java-digital signal processing (J-DSP) visual programming environment to communicate in a two-way manner with a wireless sensor network is presented. This interface was developed by writing nesC (an extension to the C programming language for sensors) code that enables J-DSP to issue commands to multiple wireless sensor motes, activate specific transducers, and analyze data using any of the existing J-DSP signal processing functions in real time. A series of exercises were developed and disseminated to provide hardware experiences to signals and systems and signal processing undergraduate students. The hardware with the J-DSP software has been used for two semesters in the senior level digital signal processing (DSP) course at Arizona State University. The interface, the exercises, and their assessment (instruments and results) are described in the paper.

Laser-scanning structural health monitoring with wireless sensor motes

A highly compact laser-scanning device that can be used as an in situ detection and monitoring device for metal fatigue is described. A prototype is built on a Mica2 wireless sensor mote platform with TinyOS-based firmware. This device is shown to be capable of detecting fatigue-related changes in the surface bidirectional reflectance distribution (BRDF) of an aluminum test coupon, and detectable changes in BRDF are measured at a very early stage of fatigue development, when no cracks larger than 50 µm in length have yet developed at the monitored location. The system power requirements are compatible with standard sensor mote architectures such as the Mica and Telos series, enabling the potential for multiyear lifetimes without battery replacement. Such an in situ optical fatigue sensor could be used in a variety of structural health monitoring applications, including aerospace, rail transport, and civil structures.

Topology Insensitive Location Determination Using Independent Estimates Through Semi-Directional Antennas

We demonstrate the effect of using multiple estimations from independent single wireless motes in order to decrease network topology dependence on location estimation in a wireless sensor network. A method of determining the location of a target by using multiple compact semi-directional antennas is shown to give an independent estimate of location from each sensor mote in a network, each estimate not relying on the data from neighboring motes as in the case of traditional triangulation. We begin by demonstrating a method of using angular diversity through multiple semi-directional antennas in order to ascertain the location of a target. The estimation of both range and angle is demonstrated in the presence of a noisy and/or faded channel. An efficient and fast algorithm on a wireless sensor mote is presented through a Taylor series expansion of the simulated antenna pattern. Furthermore, using the results from the location estimation from a single node, location determination in a realistic network is explored through both theory and simulation. The results indicate that our proposed algorithm depends significantly less on the topology (spatial arrangement) of the anchor nodes. While network planning for a variety of topologies of anchor nodes is shown to be necessary when using triangulation, our proposed algorithm is insensitive to the deployments of the anchor nodes. A testbed was created in order to experimentally demonstrate that the predictions are accurate even in triangulation-adverse topologies. The experimental testbed shows that a linear arrangement of closely spaced sensors can reduce the location error to one-fourth of the location error using triangulation