This paper proposes a low latency MAC protocol that can be used in sensor networks. To extend the lifetime of sensor nodes, the conventional solution is to synchronize active/sleep periods of all sensor nodes. However, due to these synchronized sensor nodes, packets in the intermediate nodes must wait until the next node wakes up before it can forward a packet. This induces a large delay in sensor nodes. To solve this latency problem, a clustered sensor network which uses two types of sensor nodes and layered architecture is considered. Clustered heads in each cluster are synchronized with different timing offsets to reduce the sleep delay. Using this concept, the latency problem can be solved and more efficient power usage can be obtained.

High-performance and low-cost sensors are critical devices for high-throughput analyses of bio-samples in medical diagnoses and life sciences. In this paper, we demonstrate photonic crystal nanolaser sensor, which detects the adsorption of biomolecules from the lasing wavelength shift. It is a promising device, which balances a high sensitivity, high resolution, small size, easy integration, simple setup and low cost. In particular with a nanoslot structure, it achieves a super-sensitivity in protein sensing whose detection limit is three orders of magnitude lower than that of standard surface-plasmon-resonance sensors. Our investigations indicate that the nanoslot acts as a protein condenser powered by the optical gradient force, which arises from the strong localization of laser mode in the nanoslot.

In this paper, we have proposed a new method of observing walking traces, which can observe people's indoor movement for life-logging. Particularly emphasized new techniques in this paper are methods to detect locations, where walking directions are changed, by analyzing azimuth orientations measured by an orientation sensor of an Android mobile device, and to decide walking traces by a map matching with a vector map. The experimental evaluation has shown that the proposed method can determine the correct paths of walking traces.

We introduce the distributed estimation of a random vector signal in wireless sensor networks that follow coherent multiple access channel model. We adopt the linear minimum mean squared error fusion rule. The problem of interest is to design linear coding matrices for those sensors in the network so as to minimize mean squared error of the estimated vector signal under a total power constraint. We show that the problem can be formulated as a convex optimization problem and we obtain closed form expressions of the coding matrices. Numerical results are used to illustrate the performance of the proposed method.

The primary challenges faced by wireless sensor networks are how to construct the shortest spanning tree and how to determine the optimal sink node position in terms of minimizing the data transmission times and their variances for data gathering from all sensor nodes to a sink node. To solve these two problems, we propose a novel algorithm that uses the polygonal affine shortening algorithm with flow aggregation. This algorithm enables a wireless sensor network that has movable sensor nodes and one movable sink node to self-organize the shortest spanning tree and self-determine the optimal sink node position in a fully distributed manner. We also show that our algorithm is faster than the existing shortest path algorithm in terms of computational complexity.

It becomes so important to observe a wild life for obtaining not only knowledge of its biological behaviors but also interactions with human beings in terms of geoenvironmental investigation and assessment. A sensor network is considered to be a suitable and powerful tool to monitor and observe a wild life in fields. In order to monitor/observe seabirds, a sensor network is deployed in Awashima island, Japan. A sensor platform is useful for early and quick deployment in fields. Atlas, a server-client type sensor platform, is used with several sensors, i.e., infrared sensors, thermometers within a nest and a sound sensor. The experimental results and the first outcome of observation have been reported. Particularly emphasized is that an infrared sensor has detected a leaving and returning of seabirds, and has identified that a leaving and returning is affected by sunrises and sunsets. An infrared sensed data has also shown a chick's practice before flying to the south. These facts and knowledge have not been clearly obtained by observation of human beings, so have demonstrated the usefulness of sensor networking for ecology observations.

In a wireless sensor network based on the gradient sinking model, unbalanced energy consumption is an inherent problem and can significantly reduce the network lifetime. In this letter, we propose a subcorona-based scheme to analyze the amount of received data and energy consumption of nodes on gradient sinking model. We then design an algorithm to compute the energy consumption of nodes in different subcoronas. Simulation results indicate the correctness of our proposed algorithm.

Since wireless sensor networks (WSNs) are resources-constrained, it is very essential to gather data efficiently from the WSNs so that their life can be prolonged. Data aggregation can conserve a significant amount of energy by minimizing transmission cost in terms of the number of data packets. Many applications require privacy and integrity protection of the sampled data while they travel from the source sensor nodes to a data collecting device, say a query server. However, the existing schemes suffer from high communication cost, high computation cost and data propagation delay. To resolve the problems, in this paper, we propose a new and efficient integrity protecting sensitive data aggregation scheme for WSNs. Our scheme makes use of the additive property of complex numbers to achieve sensitive data aggregation with protecting data integrity. With simulation results, we show that our scheme is much more efficient in terms of both communication and computation overheads, integrity checking and data propagation delay than the existing schemes for protecting integrity and privacy preserving data aggregation in WSNs.

This paper presents a general algorithm for pedestrian detection by on-board monocular camera which can be applied to cameras of various view ranges. Under the assumption that motion of background can be nearly approximated as a linear function, the Spatio-Temporal MRF (S-T MRF) model segments foreground objects. The foreground objects contain both pedestrian and non-pedestrian urban objects, verification was conducted by a cascaded classifier. However, the segmentation results based on motion were not exactly fit into pedestrian on the image so that shrunk or inflated pedestrian were generated. This causes errors on extracting pedestrian trajectory. For precise positioning, we implemented two types of feedback algorithm for ROI correction using the Kalman filter and the voting result of Motion-classifier and HOG-classifier. We confirmed that those ROI Corrections successfully extract precise area of pedestrian and decrease the false negative rate. Elaborately extracted pedestrian trajectory could be used as a useful source for predicting collision to pedestrian.

A novel Template Updating system for fingerprint verification systems used in mobile applications is introduced in the paper. Based on the proposed method, the system performance is improved much more than the original one. Not only the FRR (False Reject Rate) but also the small overlap problem caused by the very narrow sensor on the mobile phone are solved. Based on the template updating system, templates are replaced with matched inputs towards a target structure which can expand the coverage of templates with large displacement and rotation. By using the test database, the system performance shows the FRR can be reduced by 79% in comparison with the one without template updating procedure. This system was adopted in practical mobile phones in the commercial market in 2009.

One of the most challenging issues in wireless sensor networks is extension of the overall network lifetime. Data aggregation is one promising solution because it reduces the amount of network traffic by eliminating redundant data. In order to aggregate data, each sensor node must temporarily store received data, which requires a specific amount of memory. Most sensor nodes use static random access memory (SRAM) or flash memory for storage. SRAM can be implemented in a one-chip sensor node at low cost; however, SRAM requires standby energy, which consumes a lot of power, especially because the sensor node spends most of its time sleeping, i.e. its radio circuits are quiescent. This study proposes two types of divided SRAM: equal-size divided SRAM and equal-ratio divided SRAM. Simulations show that both proposed SRAM types offer reduced power consumption in various situations.

In Wireless Sensor Networks (WSNs), authentication is a crucial security requirement to avoid attacks against secure communication, and to mitigate against DoS attacks exploiting the limited resources of sensor nodes. Resource constraints of sensor nodes are hurdles in applying strong public key cryptographic based mechanisms in WSNs. To address the problem of authentication in WSNs, we propose an efficient and secure framework for authenticated broadcast/multicast by sensor nodes as well as for outside user authentication, which utilizes identity based cryptography and online/offline signature (OOS) schemes. The primary goals of this framework are to enable all sensor nodes in the network, firstly, to broadcast and/or multicast an authenticated message quickly; secondly, to verify the broadcast/multicast message sender and the message contents; and finally, to verify the legitimacy of an outside user. This paper reports the implementation and experimental evaluation of the previously proposed authenticated broadcast/multicast by sensor nodes scheme using online/offline signature on TinyOS and MICA2 sensor nodes.

This paper presents the design and performance evaluation of a delay attack-resilient clock synchronization scheme (abbreviated to DARCS) for wireless sensor networks. In order to provide both synchronization accuracy and robustness, we propose a novel three-way handshake-based protocol, which completely excludes non-deterministic factors such as random backoff durations and unexpected hardware interrupts in a software manner and, in this way, the node can accurately estimate the relative clock offset and the end-to-end delay between a pair of nodes. Consequently, DARCS makes it possible to correct time synchronization errors as well as to detect delay attacks precisely. The simulation results show that DARCS achieves a higher synchronization accuracy and is more resilient to delay attacks than the other popular time synchronization schemes.

This paper proposes a method for reducing redundant greedy-perimeter transitions in beacon-less geographic routing for wireless sensor networks (WSNs). Our method can be added to existing routing methods. Using a bloom filter, each node can detect a routing loop, and then the node stores the information as “failure history”. In the next forwarding the node can avoid such bad neighbors based on the failure history. Simulation results demonstrate the benefit of our method.

We consider the position estimation system for targets which exist in near wide area. The system has multiple sensors and estimates the position with multiple receivers. In the past, if receivers were arranged on a straight line, the large position error in the same direction of the line is generated. In order to reduce the error, we propose a novel estimation algorithm using transmitter's directivity information. Our system use directional emission made by an array of antennas in a transmitter. In this paper, the error characteristic which should be solved is introduced firstly. After that, our algorithm is presented. Finally the performance of the error reduction is shown by computer simulations. And we also confirm the reduction by experimental trials. The results indicate good reduction of the error.

Thin film glucose biosensors were fabricated with organic/inorganic hybrid films based on glucose oxidase (GOx) and Prussian Blue nano-clusters. The biosensors composed of hybrid films were characterized by the low operating potential and the advantage to interference-free detection. In this research, we employed two kinds of thin films for GOx immobilization: Langmuir-Blodgett (LB) and self-assembled monolayer (SAM). The LB film immobilizes GOx in its inside through the electrostatic force, while the SAM immobilizes GOx with the covalent bond. The sensors with LB film produced a relatively high current signal, while the non-linear behavior and a low stability were recognized. On the other hand, the sensors with SAM presented a good linear relationship and a very stable performance.

In wireless sensor networks constructed from battery driven nodes, it is difficult to supply electric power to the nodes. Because of this, the power consumption must be reduced. To cope with this problem, clustering techniques have been proposed. EACLE is a method that uses a clustering technique. In EACLE, route selection is executed independently after the CH (Cluster Head) selection. This two-phase control approach increases overheads and reduces the battery power, which shortens the lifetime of wireless sensor networks. To cope with this problem, we have proposed a novel routing and clustering method called PARC for wireless sensor networks that reduces these overheads by integrating the cluster selection phase and the route construction phase into a single phase. However, PARC has a weak point in that the batteries of CHs around the sink node are depleted earlier than the other nodes and the sink node cannot collect sensing data. This phenomenon is called the hot spot problem. In order to cope with this problem of PARC, we propose PARC+, which extends the CH selection method of PARC such as more nodes around the sink can be selected as a CH node. We evaluate our proposed methods by simulation experiments and show its effectiveness.

Wireless sensor networks are comprised of several sensor nodes that communicate via wireless technology. Locating the sensor nodes is a fundamental problem in developing applications for wireless sensor networks. In this paper, we introduce a distributed localization scheme, called the Rectangle Overlapping Approach (ROA), using a mobile beacon with GPS and a directional antenna. The node locations are computed by performing simple operations that rely on the rotation angle and position of the mobile beacon. Simulation results show that the proposed scheme is very efficient and that the node positions can be determined accurately when the beacon follows a random waypoint movement model.

Ridge optical waveguides (OWGs) of fluorinated polyimides were deposited on a quartz crystal microbalance (QCM), and a hybrid sensor employing the OWG spectroscopy and the QCM technique was prepared. A polyvinyl alcohol (PVA) film with CoCl2 was deposited on the OWG, and humidity sensing characteristics were investigated. White light was entered into the waveguide and the output light spectra was observed. The output light intensity markedly changed because of the chromism of CoCl2 by humidity sorption. During the output light measurement, the QCM frequency was monitored simultaneously. The humidity dependences of the QCM frequency and output light were also investigated in a range from 10% to 70%. Furthermore, the response to hydrofluoroether (HFE) was observed, and the change in the output light was hardly observed because CoCl2 does not exhibit chromism in HFE sorption.

In this review, we introduce a variety of surface sensitive techniques for the study of organic thin films, and applications to organic devices. These studies include surface plasmon emission light, organic thin film transistors, combination of quartz crystal microbalance and optical waveguide spectroscopy, evaluation of alignment of liquid crystal molecules at surfaces, and biosensor applications.