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The purpose of this paper is to propose a simple, fast, and effective method for detecting measurement errors in data collected with low-cost environmental sensors typically used in building monitoring, evaluation, and automation applications.

The method combines two unsupervised learning techniques: a distance-based anomaly detection algorithm analyzing temporal patterns in data, and a density-based algorithm comparing data across different spatially related sensors.

Results of tests using 60,000 observations of temperature and humidity collected from 20 sensors during three weeks show that the method effectively identified measurement errors and was not affected by valid unusual events. Precision, recall, and accuracy were 0.999 or higher for all cases tested.

The method is simple to implement, computationally inexpensive, and fast enough to be used in real-time with modest open-source microprocessors and a wide variety of environmental sensors. It is a robust and convenient approach for overcoming the hardware constraints of low-cost sensors, allowing users to improve the quality of collected data at almost no additional cost and effort.

The purpose of this paper is to review the use of technologies for measuring space occupancy to guide the selection of appropriate tools for workplace post-occupancy evaluation (POE) studies. The authors focus on how actual space occupancy was measured in previous studies and the pros and cons of the different technologies and tools. This paper also addresses research gaps and directions for future research.

The space occupancy measures/tools are categorized based on the three types of technologies: environmental/ambient sensors, wearable sensors/smartphones and computer vision. A total of 50 studies are reviewed to identify the capabilities and limitations of these measurements.

Based on review results, the authors propose that although sensor technology can be a useful addition to the measures/tools list, a comprehensive review of the research goal, the occupants' behavior, and the environmental settings' characteristics should be conducted beforehand. Selecting appropriate technology is critical for collecting the proper behavioral data type, with a lower level of surveillance and increased validity.

This paper urges critical thinking about existing occupancy measures/tools across various fields, to inform the adoption and creation of new building occupancy measures. The knowledge of emerging sensor technology allows researchers to better study the temporal patterns of occupant behavior over extended periods and in a wide range of settings.

The purpose of this study is to prepare various CeO₂-based carbon material (CNT, CB, GO) nanocomposites through a wet chemical process for the development of a sensor probe to detect various environmental toxins by using an electrochemical approach under room temperature conditions. A comparative study on sensitive and selective phenolic sensor (4-methoxyphenol; 4-MP) has been fabricated by modifying a glassy carbon electrode (GCE) with various nanocomposites (NCs) such as CeO₂, CeO₂–CNT (carbon nanotubes), CeO₂–CB (carbon black) and CeO₂–GO (graphene oxide) NCs.

The CeO₂–CNT NCs were prepared by the wet chemical method at low temperature. NCs were characterized by various methods such as transmission electron microscopy (TEM), Fourier-transform infra-red (FTIR), ultra-violet/visible (UV-Vis) spectroscopy and XRD (X-ray diffraction). CeO₂–CNT NCs were immobilized as a film on the flat surface of the GCE by using binders (5% Nafion). The electrochemical measurements of the 4-MP detection with the CeO₂–CNT NCs/Nafion/GCE sensor were studied by the current-voltage method.

In the optimal conditions, the sensitivity, detection limit and limit of quantification of 4-MP sensor probe were found to be 47.56 µAcm-2 µM⁻¹, 12.0 ± 0.2 nM and 40.0 ± 0.5 nM (S/N of 3), respectively.

This electrochemical sensor showed an acceptable analytical performance in the detection of 4-MP with higher sensitivity, lower detection limit, large dynamic concentration range, good reproducibility and fast response time.

This electrochemical approach can be applied practically for the determination of selective 4-MP in real environmental and extracted samples.

CeO₂–CNT NCs/Nafion/GCE sensor probe was used for the safety of environmental and health-care fields at larger scales.

This electrochemical approach is a significant achievement on the development of sensor probe. The results are indicated as being technically detailed with an up-to-date account of recent chemical sensor research studies.

Autonomous driving depends on the collection, processing and analysis of environmental information and vehicle information. Environmental perception and processing are important prerequisite for the safety of self-driving of vehicles; it involves road boundary detection, vehicle detection, pedestrian detection using sensors such as laser rangefinder, video camera, vehicle borne radar, etc.

Subjected to various environmental factors, the data clock information is often out of sync because of different data acquisition frequency, which leads to the difficulty in data fusion. In this study, according to practical requirements, a multi-sensor environmental perception collaborative method was first proposed; then, based on the principle of target priority, large-scale priority, moving target priority and difference priority, a multi-sensor data fusion optimization algorithm based on convolutional neural network was proposed.

The average unload scheduling delay of the algorithm for test data before and after optimization under different network transmission rates. It can be seen that with the improvement of network transmission rate and processing capacity, the unload scheduling delay decreased after optimization and the performance of the test results is the closest to the optimal solution indicating the excellent performance of the optimization algorithm and its adaptivity to different environments.

In this paper, the results showed that the proposed method significantly improved the redundancy and fault tolerance of the system thus ensuring fast and correct decision-making during driving.

The purpose of this paper is to provide a review of environmental sensing technologies and applications and to consider briefly the research effort.

This paper describes environmental sensing strategies and technologies for air, water quality and other monitoring applications. It concludes with a brief overview of research.

As a consequence of legislation, a technologically diverse family of sensors are used in a wide range of portable and fixed instruments to determine numerous polluting compounds entering and present in the environment. These play a critical role in protecting the environment, maintaining public health and monitoring global phenomena such as ozone depletion and artificial global warming. There is a widespread and technologically diverse research effort.

This paper provides a detailed insight into the sensors and instruments used in environmental monitoring.

This paper aims to review existing wireless sensor network (WSN) setups in various domains, focusing on affordable WSN so that it can be effectively utilised in solving the environmental problems. WSN is being explored in many applications such as home security, smart spaces, environmental monitoring, battlefield surveillance and target tracking. WSN consists of a number of tiny, low-powered, energy-constrained sensor nodes with sensing, data processing and wireless communication components. Creating a WSN setup will make the monitoring system effective and in future, it will give a roadmap for solving some common societal problems.

Various research papers in the area of WSN have been reviewed on the basis of technologies and application on different fields.

WSN was found to be the most effective solution in areas which are less explored due their hazardous nature and are difficult to reach.

This review is based on research papers available and a recent trend in the area of WSN has been explored.

Discusses the requirements in environmental monitoring ‐ primarily in aqueous environments. Detection of substances below the ppb‐level may be required. Many analytes lack intrinsic properties suitable for direct detection by a sensor. Therefore, separation, concentration, and chemical conversion may be required. Sensors may require calibration and conditioning. Efforts are taken to integrate these functions with sensor components to give integrated sensor systems, which allow unattended operation in the environment.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

Reviews the benefits and potential application of tactile sensors for use with robots.

Includes the most recent advances in both the design/manufacturing of various tactile sensors and their applications in different industries. Although these types of sensors have been adopted in a considerable number of areas, the applications such as, medical, agricultural/livestock and food, grippers/manipulators design, prosthetic, and environmental studies have gained more popularity and are presented in this paper.

Robots can perform very useful and repetitive tasks in controlled environments. However, when the robots are required to handle the unstructured and changing environments, there is a need for more elaborate means to improve their performance. In this scenario, tactile sensors can play a major role. In the unstructured environments, the robots must be able to grasp objects (or tissues, in the case of medical robots) and move objects from one location to another.

In this work, the emphasis was on the most interesting and fast developing areas of the tactile sensors applications, including, medical, agriculture and food, grippers and manipulators design, prosthetic, and environmental studies.