More recently, there has been a growing interest in the study of wireless sensor network (WSN) technologies for Interest of Things (IoT). To improve the positioning accuracy of mobile station under the non-line-of-sight (NLOS) environment, a localization algorithm based on the single-hidden layer feedforward network (SLFN) using extreme learning machine (ELM) for WSN is proposed in this paper. Optimal reduction in the time difference of arrival (TDOA) measurement error is achieved using SLFN optimized by ELM. Compared with those traditional learning algorithms, ELM has its unique feature of a higher generalization capability at a much faster learning speed. After utilizing the ELM by randomly assigning the parameters of hidden nodes in the SLFN, the competitive performance can be obtained on the optimization task for TDOA measurement error. Then, based on that result, Taylor algorithm is implemented to deal with the position problem of mobile station. Experimental results show that the effect of NLOS propagation is reduced based on our proposed algorithm by introducing the ELM into Taylor algorithm. Moreover, in the simulation, the proposed approach, called Taylor-ELM, provides better performance compared with some traditional algorithms, such as least squares, Taylor, backpropagation neural network based Taylor, and Chan positioning methods.

We have proposed an intruder detection method by using multiple-input multiple-output (MIMO) channels. Although the channel capacity for MIMO transmission is severely degraded in time-variant channels, we can take advantage of this feature in MIMO sensor applications. For MIMO sensors, the accurate estimation of channel state information (CSI) is essential. Moreover, the transceiver should be simplified from the viewpoint of saving power. Narrowband signals such as minimum shift keying (MSK) and offset quaternary phase shift keying signals are effective and are used in sensor network systems. However, because the timing and carrier offsets between the transmitter and receiver are relatively large compared to the symbol rate, accurate CSI estimation is impossible given the severe constraints imposed by the timing and carrier offsets. To solve this issue, a signal synchronization method for the CSI estimation using a narrowband MSK signal has been proposed. In this paper, we propose a new CSI estimation method for arbitrary amplitude and phase modulation schemes for the MIMO sensor. The key point of the proposed method is that control signals (unique words) are mapped so as not to pass through the origin of the complex I/Q plane. The estimation accuracy of the proposed method is evaluated via a computer simulation. Moreover, the basic performance by the proposed CSI estimation method is verified when considering intruder detection by MIMO sensor.

Energy harvesting technology was introduced into wireless sensor networks (WSNs) to solve the problem of the short lifetimes of sensor nodes. The technology gives sensor nodes the ability to convert environmental energy into electricity. Sufficient electrical energy can lengthen the lifetime and improve the quality of service of a WSN. This paper proposes a novel use of mutual information to evaluate data transmission behavior in the energy harvesting WSNs. Data at a sink for a node deteriorates over time until the next periodic transmission from the node is received. In this paper, we suggest an optimized intermittent transmission method for WSNs that harvest energy. Our method overcomes the problem of information deterioration without increasing energy cost. We show that by using spatial correlation between different sensor nodes, our proposed method can mitigate information deterioration significantly at the sink.

On March 11, 2011, a huge tsunami caused by the Great East Japan Earthquake destroyed all the electrical power facilities in the Fukushima Daiichi nuclear power plant. As a result, the reactors were badly damaged, and radioactive particles were widely scattered in the surrounding areas. In order to study the behavior of the radioactive particles emitted from the Fukushima Daiichi nuclear power plant, different measurement tools were developed. This paper describes two types of wireless radiation sensor networks and a two-dimensional radiation-level mapping system using a radio-controlled multi-copter. The measurements were analyzed, and the following conclusions were made regarding the radioactive particle distribution and its variation with time.(1) Radiation level has gradually decreased with time.(2) The rate of decrease in radiation is faster than that calculated from the half-life.(3) The radiation-level distribution is not uniform and sharply varies even within short distances such as tens of meters.(4) The locations of the hot spots have not changed, and the peak radiation levels are constantly decreasing.By using two-dimensional maps, the radiation levels can be lowered more effectively by selectively removing the highly radioactive materials. The residents can also use the map to reduce their exposure to radiation by avoiding hot spots.

This study introduces an image sensor based visible light communication (VLC) and its application to pose, position, and range estimations. There are two types of visible-light receiver: a photodiode and an image sensor. A photodiode is usually used as a reception device of VLC, and an image sensor consisting of a large number of pixels can also be used as a VLC reception device. A photodiode detects the signal intensity of incoming light, while an image sensor not only detects the incoming signal intensity but also an accurate angle of arrival of light emitted from a visible light transmitter such as a white LED light. After angles of arrival of light are detected by an image sensor, positioning and data reception can be performed. The ability of an image sensor to detect an accurate angle of arrival will provide attractive applications of VLC such as pose, position calculation, and range estimation. Furthermore, because the image sensor has the ability to spatially separate sources, outdoor positioning even with strong sunlight is possible by discarding the associated pixels of noise sources.

Activity recognition has recently been playing an important role in several research domains, especially within the healthcare system. It is important for physicians to know what their patients do in daily life. Nevertheless, existing research work has failed to adequately identify human activity because of the variety of human lifestyles. To address this shortcoming, we propose the high performance activity recognition framework by introducing a new user context and activity location in the activity log (AL2). In this paper, the user's context is comprised by context-aware infrastructure and human posture. We propose a context sensor network to collect information from the surrounding home environment. We also propose a range-based algorithm to classify human posture for combination with the traditional user's context. For recognition process, ontology-based activity recognition (OBAR) is developed. The ontology concept is the main approach that uses to define the semantic information and model human activity in OBAR. We also introduce a new activity log ontology, called AL2 for investigating activities that occur at the user's location at that time. Through experimental studies, the results reveal that the proposed context-aware activity recognition engine architecture can achieve an average accuracy of 96.60%.

This paper presents a method to seamlessly extend the coverage of energy supply field for wireless sensor networks in order to free sensors from wires and batteries, where the multi-point scheme is employed to overcome path-loss attenuation, while the carrier shift diversity is introduced to mitigate the effect of interference between multiple wave sources. As we focus on the energy transmission part, sensor or communication schemes are out of scope of this paper. To verify the effectiveness of the proposed wireless energy transmission, this paper conducts indoor experiments in which we compare the power distribution and the coverage performance of different energy transmission schemes including conventional single-point, simple multi-point and our proposed multi-point scheme. To easily observe the effect of the standing-wave caused by multipath and interference between multiple wave sources, 3D measurements are performed in an empty room. The results of our experiments together with those of a simulation that assumes a similar antenna setting in free space environment show that the coverage of single-point and multi-point wireless energy transmission without carrier shift diversity are limited by path-loss, standing-wave created by multipath and interference between multiple wave sources. On the other hand, the proposed scheme can overcome power attenuation due to the path-loss as well as the effect of standing-wave created by multipath and interference between multiple wave sources.

In mobile wireless sensor networks, coverage and energy are two significant factors determining network performance. When taking both factors into account, the challenges include how to select and migrate nodes to keep coverage quality, how to forecast and prevent potential coverage holes and how to use energy control in mobile networks. In this paper, we propose a new Coverage Maintenance and Energy Control (CMEC) algorithm to achieve and keep high coverage quality and energy efficiency. For CMEC, we provide a new cost metric for selecting migration nodes. Our simulation results confirm that our algorithm improves coverage performance and lifetime of network.

This paper presents a data gathering protocol for wireless sensor network applications that require high throughput and topology adaptability under the premises of uniform traffic and energy-rich environments. Insofar as high throughput is concerned, TDMA is more suitable than CSMA. However, traditional TDMA protocols require complex scheduling of transmission time slots. The scheduling burden is the primary barrier to topology adaptability. Under the premises of uniform traffic and energy-rich environments, this paper proposes a token-scheduled multi-channel TDMA protocol named TKN-TWN to ease the scheduling burden while exploiting the advantages of TDMA. TKN-TWN uses multiple tokens to arbitrate data transmission. Due to the simplified scheduling based on tokens, TKN-TWN is able to provide adaptability for topology changes. The contention-free TDMA and multi-channel communication afford TKN-TWN the leverage to sustain high throughput based on pipelined packet forwarding. TKN-TWN further associates the ownership of tokens with transmission slot assignment toward throughput optimization. We implement TKN-TWN on Tmote Sky with TinyOS 2.1.1 operating system. Experimental results in a deployed network consisting of 32 sensor nodes show that TKN-TWN is robust to network changes caused by occasional node failures. Evaluation also shows that TKN-TWN is able to provide throughput of 9.7KByte/s.

Sensor noise prevents the exact measurement of output, which makes it difficult to guarantee the ultimate bound of the actual output and states, which is smaller than the sensor noise amplitude. Even worse, the time-varying delay in the input does not guarantee the boundedness of the actual output and states under sensor noise. In this letter, our considered system is a chain of integrators in which time-varying delay exists in the input and there is an additive form of sensor noise in the output measurement. To guarantee the arbitrarily small ultimate bound of the actual output and states, we newly propose an adaptive output feedback controller whose gain is tuned on-line. The merits of our control method over the existing results are clearly shown in the example.

Landslides during heavy rainfall cause a great amount of damage in terms of both property and human life. To predict landslide disasters, we designed and implemented a wireless sensor network using our existing highly fault tolerant ad-hoc network. Since many sensors must be used, we propose a new MAC protocol that allows the network to support more sensor terminals. Our protocol is a hybrid CSMA/Psuedo-TDMA scheme which allows the terminals to decide their transmission timing independently in a random fashion. A timing beacon is not required, so power consumption can be reduced. Simulation results show that the number of terminals supported by the network can be greatly increased.

We consider the problem of optimizing the quantizer design for distributed estimation systems where all nodes located at different sites collect measurements and transmit quantized data to a fusion node, which then produces an estimate of the parameter of interest. For this problem, the goal is to minimize the amount of information that the nodes have to transmit in order to attain a certain application accuracy. We propose an iterative quantizer design algorithm that seeks to find a non-regular mapping between quantization partitions and their codewords so as to minimize global distortion such as the estimation error. We apply the proposed algorithm to a system where an acoustic amplitude sensor model is employed at each node for source localization. Our experiments demonstrate that a significant performance gain can be achieved by our technique as compared with standard typical designs and even with distributed novel designs recently published.

The complicated indoor environment such as obstacles causes the non-line of sight (NLOS) environment. In this paper, we propose a voting matrix based residual weighting (VM-Rwgh) algorithm to mitigate NLOS errors in indoor localization system. The voting matrix is employed to provide initial localization results. The residual weighting is used to improve the localization accuracy. The VM-Rwgh algorithm can overcome the effects of NLOS errors, even when more than half of the measurements contain NLOS errors. Simulation results show that the VM-Rwgh algorithm provides higher location accuracy with relatively lower computational complexity in comparison with other methods.

We review our recent achievements in monolithic 3D-ICs and flexible electronics based on single-grain Si TFTs that are fabricated inside a single-grain with a low-temperature process. Based on pulsed-laser crystallization and submicron sized cavities made in the substrate, amorphous-Si precursor film was converted into poly-Si having grains that are formed on predetermined positions. Using the method called µ-Czochralski process and LPCVD a-Si precursor film, two layers of the SG Si TFT layers with the grains having a diameter of 6µm were vertically stacked with a maximum process temperature of 550°C. Mobility for electrons and holes were 600cm2/Vs and 200cm2/Vs, respectively. As a demonstration of monolithic 3D-ICs, the two SG-TFT layers were successfully implemented into CMOS inverter, 3D 6T-SRAM and single-grain lateral PIN photo-diode with in-pixel amplifier. The SG Si TFTs were applied to flexible electronics. In this case, the a-Si precursor was prepared by doctor-blade coating of liquid-Si based on pure cyclopentasilane (CPS) on a polyimide (PI) substrate with maximum process temperature of 350°C. The µ-Czochralski process provided location-controlled Si grains with a diameter of 3µm and mobilities of 460 and 121cm2/Vs for electrons and holes, respectively, were obtained. The devices on PI were transferred to a plastic foil which can operate with a bending diameter of 6mm. Those results indicate that the SG TFTs are attractive for their use in both monolithic 3D-ICs and flexible electronics.

A self-powered urinary-incontinence sensor with a flexible wire-type urine-activated battery has been developed as an application for wireless biosensor networks. It is disposable and can be embedded in a diaper. The battery consists of two long film-type line electrodes printed on a flexible plastic sheet that abuts the absorbent material of the diaper. It conforms to the shape of the diaper when the diaper is worn. The stress produced by the curvature of the diaper presses the electrodes firmly against the diaper material, providing greater contact with any urine present. Thus, the battery generates more power than when it is flat, as in an unworn diaper. To verify the effectiveness of the battery, we fabricated a battery and a prototype sensor, which consists of an intermittent-power-supply circuit and a wireless transmitter, and embedded the battery in a diaper. The anode of the battery also acts as a wide ground plane for the antenna of the wireless transmitter, which radiates a large amount of power. When 80cc of urine is poured onto the diaper, the battery outputs a voltage of around 1V, which allows the sensor to transmit an ID signal over a distance of 5m every 40 seconds or so.

A promising application of a single-flux quantum (SFQ) circuit is read-out circuitry for a multi-channel superconductive sensor array. In such applications, the SFQ read-out circuit is expected to operate outside a magnetic shield. We investigated an SFQ circuit structure, which is tolerant to an external magnetic field, using the AIST 2.5kA/cm2 Nb standard 2 process, which has four Nb wiring layers including the ground plane. By covering the entire circuit using an upper Nb wiring layer called the control (CTL) layer, the influences of the external magnetic field on the SFQ circuit operation can be avoided. We experimentally evaluated the sheet inductance of the wiring layer underneath the CTL shielding layer to design a magnetic-field-tolerant SFQ circuit. We implemented and measured test circuits comprising toggle flip-flops (TFFs) to evaluate their magnetic field tolerances. The operating margin and maximum operating frequency of the designed TFF did not deteriorate with increases in the magnetic field applied to the test circuit, whereas the operating margin of the conventional TFF was reduced by applying the magnetic field. We have also demonstrated the high-speed operation of the designed TFF operated in an unshielded environment at a frequency of up to 120GHz with a wide operating margin.

To visualize the biochemical distribution two-dimensionally, we invented a solid-state-type ion image sensor that indicates the chemical activity of solutions and cells. The device, which consists of a CCD array covered with a functionalized membrane to detect charge accumulation, is highly sensitive to changes in the concentration and two-dimensional distribution of ions and biomaterials.

Methods for in-network joins of sensing data with tuples, in partitioned condition tables stored in sensor nodes, have been studied for efficient event detection. A recently proposed method performs the join operation after distributing the tuples of a condition table evenly among homogeneous sensor nodes with the same storage capacity. In the method, the condition table is horizontally partitioned, and each partition is allocated to the corresponding node, along the path from the highest level to the leaf level. If the path length is larger than the number of partitions, the second round distribution of the partitions resumes from the node at the next level, and so on. Thus, the last node at each round can be assigned the partition that is smaller than the others, which would otherwise cause wasted internal fragmentation. Further, little research has been conducted on methods for the cases of heterogeneous sensor nodes with different available spaces, as well as the vertical partitioning of condition table. In this study, we propose a method of partitioning a condition table that utilizes the internal fragmentation, by treating the tuples of a condition table as a circular list. The proposed method is applicable to the case in which nodes have different available spaces. Furthermore, a new method for vertically partitioning a condition table is suggested. Experiments verify the reduction in the data transmission amount offered by the proposed methods, as compared to existing methods.

Gait-based owner authentication using accelerometers has recently been extensively studied owing to the development of wearable electronic devices. An actual gait signal is always subject to change due to many factors including variation of sensor attachment. In this research, we tackle to the practical sensor-orientation inconsistency, for which signal sequences are captured at different sensor orientations. We present an iterative signal matching algorithm based on phase-registration technique to simultaneously estimate relative sensor-orientation and register the 3D acceleration signals. The iterative framework is initialized by using 1D orientation-invariant resultant signals which are computed from 3D signals. As a result, the matching algorithm is robust to any initial sensor-orientation. This matching algorithm is used to match a probe and a gallery signals in the proposed owner authentication method. Experiments using actual gait signals under various conditions such as different days, sensors, weights being carried, and sensor orientations show that our authentication method achieves positive results.

Packet loss and energy dissipation are two major challenges of designing large-scale wireless sensor networks. Since sensing data is spatially correlated, compressed sensing (CS) is a promising reconstruction scheme to provide low-cost packet error correction and load balancing. In this letter, assuming a multi-hop network topology, we present a CS-oriented data aggregation scheme with a new measurement matrix which balances energy consumption of the nodes and allows for recovery of lost packets at fusion center without additional transmissions. Comparisons with existing methods show that the proposed scheme offers higher recovery precision and less energy consumption on TinyOS.