In this paper, we propose a new compression method using underwater acoustic sensor signals for underwater surveillance. Generally, sonar applications that are used for surveillance or ocean monitoring are composed of many underwater acoustic sensors...
This paper presents a compression method for inertial and magnetic sensor data, where the compressed data are used to estimate some states. When sensor data are bounded, the proposed compression method guarantees that the compression error is smaller...
Compression therapy is widely used as the gold standard for management of chronic venous insufficiency and venous leg ulcers, and the amount of pressure applied during the compression therapy is crucial in supporting healing. A fibre optic pressure s...
There are currently no evidence-based practical automated injury risk factor estimation tools to monitor low back compressive force in ambulatory or sporting environments. For this purpose, inertial sensors may potentially replace laboratory-based sy...
This paper presents a scalable embedded solution for processing and transferring 3D point cloud data. Sensors based on the time-of-flight principle generate data which are processed on a local embedded computer and compressed using an octree-based sc...
Data compression is very important in wireless sensor networks (WSNs) with the limited energy of sensor nodes. Data communication results in energy consumption most of the time; the lifetime of sensor nodes is usually prolonged by reducing data trans...
Energy is an important consideration in wireless sensor networks. In the current compression evaluations, traditional indices are still used, while energy efficiency is probably neglected. Moreover, various evaluation biases significantly affect the...
With the goal of addressing the issue of image compression in wireless multimedia sensor networks with high recovered quality and low energy consumption, an image compression and transmission scheme based on non-negative matrix factorization (NMF) is...
We propose a technique to optimize the energy efficiency of data collection in sensor networks by exploiting a selective data compression. To achieve such an aim, we need to make optimal decisions regarding two aspects: (1) which sensor nodes should...
Target tracking is a critical wireless sensor application, which involves signal and information processing technologies. In conventional target position estimation methods, an estimate is usually demonstrated by an average target position. In contra...
The use of sensor applications has been steadily increasing, leading to an urgent need for efficient data compression techniques to facilitate the storage, transmission, and processing of digital signals generated by sensors. Unlike other sequential...
In this article a scheme for image transmission over Wireless Sensor Networks (WSN) with an adaptive compression factor is introduced. The proposed control architecture affects the quality of the transmitted images according to: (a) the traffic load...
Congestion in a wireless sensor network causes an increase in the amount of data loss and delays in data transmission. In this paper, we propose a new congestion control technique (ACT, Adaptive Compression-based congestion control Technique) based o...
Emerging IoT (Internet of Things) technologies have enjoyed tremendous success in a variety of applications. Since sensors in IoT consume a lot of energy to transmit their data, data compression used to prolong system lifetime has become a hot resear...
Neuromorphic Vision Sensors (NVSs) are emerging sensors that acquire visual information asynchronously when changes occur in the scene. Their advantages versus synchronous capturing (frame-based video) include a low power consumption, a high dynamic...
Wireless sensor networks (WSNs) have been widely used to monitor the environment, and sensors in WSNs are usually power constrained. Because inner-node communication consumes most of the power, efficient data compression schemes are needed to reduce...
In this paper, we propose a bit depth compression (BDC) technique, which performs bit packing by dynamically determining the pack size based on the pattern of the bit depth level of the sensor data, thereby maximally reducing the space wastage that m...
Virtual sensor technology, which uses simulation models/algorithms to calculate a value to represent an unmeasured variable or replace a directly measured reading, has attracted many studies in the heating, ventilation, air conditioning and refrigera...
Much research is still underway to achieve long-term and real-time monitoring using data from vision-based sensors. A major challenge is handling and processing enormous amount of data and images for either image storage, data transfer, or image anal...
Data compression is a useful method to reduce the communication energy consumption in wireless sensor networks (WSNs). Most existing neural network compression methods focus on improving the compression and reconstruction accuracy (i.e., increasing p...
Wireless rechargeable sensor nodes can collect additional data, which leads to an increase in the precision of data analysis, when enough harvested energy is acquired. However, because such nodes increase the amount of sensory data, some nodes (espec...
A node in a solar-powered wireless sensor network (WSN) collects energy when the sun shines and stores it in a battery or capacitor for use when no solar power is available, in particular at night. In our scheme, each tiny node in a WSN periodically...
High-frequency sampling in mechanical vibration wireless sensor networks (WSNs) generates large volumes of raw data, imposing substantial demands on transmission bandwidth and node energy consumption. To address this problem, this paper proposes a tw...
There is an increasing need to accurately measure compressive force for biomedical and industrial applications. However, this need has not been fully addressed, as many sensors are bulky, have high power requirements, and/or are susceptible to electr...
Embedded sensors are widely employed for the structural health monitoring of structures constructed with concrete or mortar. Despite embedded sensors being actively used, there has been no study on whether or not the sensor probe placement within str...
The compressive sensing (CS) paradigm uses simultaneous sensing and compression to provide an efficient image acquisition technique. The main advantages of the CS method include high resolution imaging using low resolution sensor arrays and faster im...
Recent advancements in sensor technology have led to an increase in embedding sensors into construction materials for monitoring purposes in the construction industry. However, systematic research on the resulting changes to the material properties i...
Women sports wearer’s comfort and health are greatly impacted by the breast movements and resultant sports bra compression to prevent excessive movement. However, as sports bras are only made in universal sizes, they do not offer the right kind...
Information acquisition in underwater sensor networks is usually limited by energy and bandwidth. Fortunately, the received signal can be represented sparsely on some basis. Therefore, a compressed sensing method can be used to collect the informatio...
A compressive sensing joint sparse representation direction of arrival estimation (CSJSR-DoA) approach is proposed for wireless sensor array networks (WSAN). By exploiting the joint spatial and spectral correlations of acoustic sensor array data, the...
It is important to reduce the time cost of video compression for image sensors in video sensor network. Motion estimation (ME) is the most time-consuming part in video compression. Previous work on ME exploited intra-frame data reuse in a reference...
Surface wave velocity measurement of concrete using ultrasonic sensors requires testing on only one side of a member. Thus, it is applicable to concrete cast inside a form and is often used to detect flaws and evaluate the compressive strength of har...
Electromyography (EMG) sensors produce a stream of data at rates that can easily saturate a low-energy wireless link such as Bluetooth Low Energy (BLE), especially if more than a few EMG channels are being transmitted simultaneously. Compressing data...
As the technology for offshore wireless transmission and collaborative innovation in unmanned ships continues to mature, research has been gradually carried out in various countries on methods of compressing and transmitting perceptual video while dr...
Compressed sensing based in-network compression methods which minimize data redundancy are critical to cognitive video sensor networks. However, most existing methods require a large number of sensors for each measurement, resulting in significant pe...
Clinical rehabilitation assessment is an important part of the therapy process because it is the premise for prescribing suitable rehabilitation interventions. However, the commonly used assessment scales have the following two drawbacks: (1) they ar...
We propose a new harvesting approach for Vehicular Sensor Networks based on compressed sensing (CS) technology called Compressed Sensing-based Vehicular Data Harvesting (CS-VDH). This compression technology allows for the reduction of the information...
Due to specific dynamics of the operating environment and required safety regulations, the amount of acquired data of an automotive LiDAR sensor that has to be processed is reaching several Gbit/s. Therefore, data compression is much-needed to enable...
Underwater sensors that detect the distance and direction of acoustic sources are critical for surveillance monitoring and target detection in the water. Here, we propose an axial vector sensor that utilizes a small (~1 cm3) compressive-type piezoele...
In this paper, we consider the problem of reconstructing the temporal and spatial profile of some physical phenomena monitored by large-scale Wireless Sensor Networks (WSNs) in an energy efficient manner. Compressive sensing is one of the popular cho...
Compressed sensing is widely used in modern resource-constrained sensor networks. However, achieving high-quality and robust signal reconstruction under low sampling rates and noise interference remains challenging. Traditional CS methods have limite...
Structural health monitoring (SHM) with a dense sensor network and repeated vibration measurements produces lots of data that have to be stored. If the sensor network is redundant, data compression is possible by storing the signals of selected Bayes...
Compressive sensing (CS) provides an energy-efficient paradigm for data gathering in wireless sensor networks (WSNs). However, the existing work on spatial-temporal data gathering using compressive sensing only considers either multi-hop relaying bas...
The transmission of high-volume multimedia content (e.g., images) is challenging for a resource-constrained wireless multimedia sensor network (WMSN) due to energy consumption requirements. Redundant image information can be compressed using traditio...
Devices in a visual sensor network (VSN) are mostly powered by batteries, and in such a network, energy consumption and bandwidth utilization are the most critical issues that need to be taken into consideration. The most suitable solution to such is...
The development of compressive sensing (CS) technology has inspired data gathering in wireless sensor networks to move from traditional raw data gathering towards compression based gathering using data correlations. While extensive efforts have been...
This work combines compressive sensing and short word-length techniques to achieve localization and target tracking in wireless sensor networks with energy-efficient communication between the network anchors and the fusion center. Gradient descent lo...
We consider a Wireless Sensor Network (WSN) monitoring environmental data. Compressive Sensing (CS) is explored to reduce the number of coefficients to transmit and consequently save the energy of sensor nodes. Each sensor node collects N samples of...
In designing wireless sensor networks (WSNs), it is important to reduce energy dissipation and prolong network lifetime. Clustering of nodes is one of the most effective approaches for conserving energy in WSNs. Cluster formation protocols generally...
An ultra-high-speed computational CMOS image sensor with a burst frame rate of 303 megaframes per second, which is the fastest among the solid-state image sensors, to our knowledge, is demonstrated. This image sensor is compatible with ordinary singl...
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