Ömer Galip Saracoglu and Hayriye Altural
Article: Color Regeneration from Reflective Color Sensor Using an Artificial Intelligent Technique
Sensors 2010, 10(9), 8363-8374; doi:10.3390/s100908363 - published online 3 September 2010
Show/Hide AbstractAbstract: A low-cost optical sensor based on reflective color sensing is presented. Artificial neural network models are used to improve the color regeneration from the sensor signals. Analog voltages of the sensor are successfully converted to RGB colors. The artificial intelligent models presented in this work enable color regeneration from analog outputs of the color sensor. Besides, inverse modeling supported by an intelligent technique enables the sensor probe for use of a colorimetric sensor that relates color changes to analog voltages.

Yong Feng, Ming Liu, Xiaomin Wang and Haigang Gong
Article: Minimum Expected Delay-Based Routing Protocol (MEDR) for Delay Tolerant Mobile Sensor Networks
Sensors 2010, 10(9), 8348-8362; doi:10.3390/s100908348 - published online 3 September 2010
Show/Hide AbstractAbstract: It is a challenging work to develop efficient routing protocols for Delay Tolerant Mobile Sensor Networks (DTMSNs), which have several unique characteristics such as sensor mobility, intermittent connectivity, energy limit, and delay tolerability. In this paper, we propose a new routing protocol called Minimum Expected Delay-based Routing (MEDR) tailored for DTMSNs. MEDR achieves a good routing performance by finding and using the connected paths formed dynamically by mobile sensors. In MEDR, each sensor maintains two important parameters: Minimum Expected Delay (MED) and its expiration time. According to MED, messages will be delivered to the sensor that has at least a connected path with their hosting nodes, and has the shortest expected delay to communication directly with the sink node. Because of the changing network topology, the path is fragile and volatile, so we use the expiration time of MED to indicate the valid time of the path, and avoid wrong transmissions. Simulation results show that the proposed MEDR achieves a higher message delivery ratio with lower transmission overhead and data delivery delay than other DTMSN routing approaches.

Klemen Kozmus Trajkovski, Oskar Sterle and Bojan Stopar
Article: Sturdy Positioning with High Sensitivity GPS Sensors Under Adverse Conditions
Sensors 2010, 10(9), 8332-8347; doi:10.3390/s100908332 - published online 3 September 2010
Show/Hide AbstractAbstract: High sensitivity GPS receivers have extended the use of GNSS navigation to environments which were previously deemed unsuitable for satellite signal reception. Under adverse conditions the signals become attenuated and reflected. High sensitivity receivers achieve signal reception by using a large number of correlators and an extended integration time. Processing the observation data in dynamic and rapidly changing conditions requires a careful and consistent treatment. Code-based autonomous solutions can cause major errors in the estimated position, due primarily to multipath effects. A custom procedure of autonomous GPS positioning has been developed, boosting the positioning performance through appropriate processing of code and Doppler observations. Besides the common positioning procedures, robust estimation methods have been used to minimise the effects of gross observation errors. In normal conditions, differential GNSS yields good results, however, under adverse conditions, it fails to improve significantly the receiver’s position. Therefore, a so-called conditional DGPS has been developed which determines the position differentially by using data from the strong signals only. These custom-developed procedures have been tested in different conditions in static and kinematic cases and the results have been compared to those processed by the receiver.

Daniel G. Costa and Luiz Affonso Guedes
Review: The Coverage Problem in Video-Based Wireless Sensor Networks: A Survey
Sensors 2010, 10(9), 8215-8247; doi:10.3390/s100908215 - published online 2 September 2010
Show/Hide AbstractAbstract: Wireless sensor networks typically consist of a great number of tiny low-cost electronic devices with limited sensing and computing capabilities which cooperatively communicate to collect some kind of information from an area of interest. When wireless nodes of such networks are equipped with a low-power camera, visual data can be retrieved, facilitating a new set of novel applications. The nature of video-based wireless sensor networks demands new algorithms and solutions, since traditional wireless sensor networks approaches are not feasible or even efficient for that specialized communication scenario. The coverage problem is a crucial issue of wireless sensor networks, requiring specific solutions when video-based sensors are employed. In this paper, it is surveyed the state of the art of this particular issue, regarding strategies, algorithms and general computational solutions. Open research areas are also discussed, envisaging promising investigation considering coverage in video-based wireless sensor networks.

Jesus Roberto Millan-Almaraz, Rene de Jesus Romero-Troncoso, Ramon Gerardo Guevara-Gonzalez, Luis Miguel Contreras-Medina, Roberto Valentin Carrillo-Serrano, Roque Alfredo Osornio-Rios, Carlos Duarte-Galvan, Miguel Angel Rios-Alcaraz and Irineo Torres-Pacheco
Article: FPGA-based Fused Smart Sensor for Real-Time Plant-Transpiration Dynamic Estimation
Sensors 2010, 10(9), 8316-8331; doi:10.3390/s100908316 - published online 2 September 2010
Show/Hide AbstractAbstract: Plant transpiration is considered one of the most important physiological functions because it constitutes the plants evolving adaptation to exchange moisture with a dry atmosphere which can dehydrate or eventually kill the plant. Due to the importance of transpiration, accurate measurement methods are required; therefore, a smart sensor that fuses five primary sensors is proposed which can measure air temperature, leaf temperature, air relative humidity, plant out relative humidity and ambient light. A field programmable gate array based unit is used to perform signal processing algorithms as average decimation and infinite impulse response filters to the primary sensor readings in order to reduce the signal noise and improve its quality. Once the primary sensor readings are filtered, transpiration dynamics such as: transpiration, stomatal conductance, leaf-air-temperature-difference and vapor pressure deficit are calculated in real time by the smart sensor. This permits the user to observe different primary and calculated measurements at the same time and the relationship between these which is very useful in precision agriculture in the detection of abnormal conditions. Finally, transpiration related stress conditions can be detected in real time because of the use of online processing and embedded communications capabilities.

Rong Zhu, Henggao Ding, Yan Su and Yongjun Yang
Article: Modeling and Experimental Study on Characterization of Micromachined Thermal Gas Inertial Sensors
Sensors 2010, 10(9), 8304-8315; doi:10.3390/s100908304 - published online 2 September 2010
Show/Hide AbstractAbstract: Micromachined thermal gas inertial sensors based on heat convection are novel devices that compared with conventional micromachined inertial sensors offer the advantages of simple structures, easy fabrication, high shock resistance and good reliability by virtue of using a gaseous medium instead of a mechanical proof mass as key moving and sensing elements. This paper presents an analytical modeling for a micromachined thermal gas gyroscope integrated with signal conditioning. A simplified spring-damping model is utilized to characterize the behavior of the sensor. The model relies on the use of the fluid mechanics and heat transfer fundamentals and is validated using experimental data obtained from a test-device and simulation. Furthermore, the nonideal issues of the sensor are addressed from both the theoretical and experimental points of view. The nonlinear behavior demonstrated in experimental measurements is analyzed based on the model. It is concluded that the sources of nonlinearity are mainly attributable to the variable stiffness of the sensor system and the structural asymmetry due to nonideal fabrication.