An IoT measurement solution for continuous indoor environmental quality monitoring for buildings renovation

The measurement of Indoor Environmental Quality (IEQ) requires the acquisition of multiple quantities regarding thermal comfort and indoor air quality. The IEQ monitoring is essential to investigate the building’s performance, especially when renovation is needed to improve energy efficiency and occupants’ well-being. Thus, IEQ data should be acquired for long periods inside occupied buildings, but traditional measurement solutions could not be adequate. This paper presents the development and application of a non-intrusive and scalable IoT sensing solution for continuous IEQ measurement in occupied buildings during the renovation process. The solution is composed of an IR scanner for mean radiant temperature measurement and a desk node with environmental sensors (air temperature, relative humidity, CO2, PMs). The integration with a BIM-based renovation approach was developed to automatically retrieve building’s data required for sensor configuration and KPIs calculation. The system was installed in a nursery located in Poland to support the renovation process. IEQ performance measured before the intervention revealed issues related to radiant temperature and air quality. Using measured data, interventions were realized to improve the envelope insulation and the occupant’s behaviour. Results from post-renovation measurements showed the IEQ improvement achieved, demonstrating the impact of the sensing solution.

UAV low-altitude obstacle detection based on the fusion of LiDAR and camera

In this paper, aiming at the flying scene of the small unmanned aerial vehicle (UAV) in the low-altitude suburban environment, we choose the sensor configuration scheme of LiDAR and visible light camera, and design the static and dynamic obstacle detection algorithms based on sensor fusion. For static obstacles such as power lines and buildings in the low-altitude environment, the way that image-assisted verification of point clouds is used to fuse the contour information of the images and the depth information of the point clouds to obtain the location and size of static obstacles. For unknown dynamic obstacles such as rotary-wing UAVs, the IMM-UKF algorithm is designed to fuse the distance measurement information of point clouds and the high precision angle measurement information of image to achieve accurate estimation of the location and velocity of the dynamic obstacles. We build an experimental platform to verify the effectiveness of the obstacle detection algorithm in actual scenes and evaluate the relevant performance indexes.

Sensors in Autonomous Vehicles: A Survey

Research and technology in autonomous vehicles is beginning to become well recognized among computer scientists and engineers. Autonomous vehicles contain combination of GPS, LIDAR, cameras, RADAR and ultrasonic sensors (which are hardly ever included). These autonomous vehicles use no less than two sensing modalities, and usually have three or more. The goal of this research is to determine which sensor to use depending on the functionality of the autonomous vehicle and analyze the simi- larities and differences of sensor configurations (which may come from different industries too). This study summarizes sensors in four industries: personal vehicles, public transportation, smart farming, and logistics. In addition, the paper includes advantages and disadvantages of how each sensor configuration are helpful by taking into considerations the activity that has to be achieved in the autonomous vehicle. A table of results is incorporated to organize most of the sensors' availability in the market and their advantages and disadvantages. After comparing each sensor configuration, recommendations are going to be proposed for different scenarios in which some types of sensors will be more useful than others.

A multi-point heart rate monitoring using a soft wearable system based on fiber optic technology

Early diagnosis can be crucial to limit both the mortality and economic burden of cardiovascular diseases. Recent developments have focused on the continuous monitoring of cardiac activity for a prompt diagnosis. Nowadays, wearable devices are gaining broad interest for a continuous monitoring of the heart rate (HR). One of the most promising methods to estimate HR is the seismocardiography (SCG) which allows to record the thoracic vibrations with high non-invasiveness in out-of-laboratory settings. Despite significant progress on SCG, the current state-of-the-art lacks both information on standardized sensor positioning and optimization of wearables design. Here, we introduce a soft wearable system (SWS), whose novel design, based on a soft polymer matrix embedding an array of fiber Bragg gratings, provides a good adhesion to the body and enables the simultaneous recording of SCG signals from multiple measuring sites. The feasibility assessment on healthy volunteers revealed that the SWS is a suitable wearable solution for HR monitoring and its performance in HR estimation is strongly influenced by sensor positioning and improved by a multi-sensor configuration. These promising characteristics open the possibility of using the SWS in monitoring patients with cardiac pathologies in clinical (e.g., during cardiac magnetic resonance procedures) and everyday life settings.

Proposal for a Skin Layer-Wise Decomposition Model of Spatially-Resolved Diffuse Reflectance Spectra Based on Maximum Depth Photon Distributions: A Numerical Study

In the context of cutaneous carcinoma diagnosis based on in vivo optical biopsy, Diffuse Reflectance (DR) spectra, acquired using a Spatially Resolved (SR) sensor configuration, can be analyzed to distinguish healthy from pathological tissues. The present contribution aims at studying the depth distribution of SR-DR-detected photons in skin from the perspective of analyzing how these photons contribute to acquired spectra carrying local physiological and morphological information. Simulations based on modified Cuda Monte Carlo Modeling of Light transport were performed on a five-layer human skin optical model with epidermal thickness, phototype and dermal blood content as variable parameters using (i) wavelength-resolved scattering and absorption properties and (ii) the geometrical configuration of a multi-optical fiber probe implemented on an SR-DR spectroscopic device currently used in clinics. Through histograms of the maximum probed depth and their exploitation, we provide numerical evidence linking the characteristic penetration depth of the detected photons to their wavelengths and four source–sensor distances, which made it possible to propose a decomposition of the DR signals related to skin layer contributions.

Biosensing Using SERS Active Gold Nanostructures

Surface-enhanced Raman spectroscopy (SERS) has become a powerful tool for biosensing applications owing to its fingerprint recognition, high sensitivity, multiplex detection, and biocompatibility. This review provides an overview of the most significant aspects of SERS for biomedical and biosensing applications. We first introduced the mechanisms at the basis of the SERS amplifications: electromagnetic and chemical enhancement. We then illustrated several types of substrates and fabrication methods, with a focus on gold-based nanostructures. We further analyzed the relevant factors for the characterization of the SERS sensor performances, including sensitivity, reproducibility, stability, sensor configuration (direct or indirect), and nanotoxicity. Finally, a representative selection of applications in the biomedical field is provided.

Optimization Strategy of IoT Sensor Configuration Based on Genetic Algorithm-Neural Network

This article carries out the overall design framework of the IoT sensor data processing platform and analyzes the advantages of using the integrated construction platform. The platform is divided into two parts, a web management platform and a data communication system, and interacts with the database by integrating the business layers of the two into one. The web management platform provides configurable communication protocol customization services, equipment information, personal information, announcement information management services, and data collection information monitoring and analysis services. The collected data is analyzed by the sensor data communication service system and then provided to the web management platform for query and call. This paper discusses the theoretical basis of the combination of genetic algorithm and neural network and proposes the necessity of improving genetic algorithm. The improved level involves chromosome coding methods, fitness function selection, and genetic manipulation. We propose an improved genetic algorithm and use an improved genetic algorithm (IGA) to optimize the neural network structure. The finite element method is adopted, the finite element model is established, and the shock piezoelectric response is numerically simulated. The genetic neural network method is used to simulate the collision damage location detection problem. The piezoelectric sensor is optimized, and the optimal sensor configuration corresponding to its initial layout is obtained, which provides guidance for the optimal configuration of the actual piezoelectric sensor.

Bovine Serum Albumin Protein Detection by a Removable SPR Chip Combined with a Specific MIP Receptor

Nowadays, the development of simple, fast, and low-cost selective sensors to detect substances of interest is of great importance in several application fields. Among this kind of sensors, those based on surface plasmon resonance (SPR) represent a promising category, since they are highly sensitive, versatile, and label-free. In this work, an SPR probe, based on a poly(methyl methacrylate) (PMMA) slab waveguide covered by a gold nanofilm, combined with a specific molecularly imprinted polymer (MIP) receptor for bovine serum albumin (BSA) protein, has been realized and experimentally characterized. The obtained experimental results have shown a limit of detection (LOD) equal to about 8.5 × 10−9 M. This value is smaller than the one achieved by another SPR probe, based on a D-shaped plastic optical fiber (POF), functionalized with the same MIP receptor; more specifically, the obtained LOD was reduced by about three orders of magnitude with respect to the POF configuration. Moreover, concerning the D-shaped POF configuration, no manufacturing process is present in the proposed sensor configuration. In addition, fibers are used only to connect the simple sensor chip with a light source and a detector, promoting a bio-chemical sensing approach based on disposable, low-cost, and removable chips.