scholarly journals Assessing the value of complex refractive index and particle density for calibration of low-cost particle matter sensor for size-resolved particle count and PM2.5 measurements

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259745
Author(s):  
Ching-Hsuan Huang ◽  
Jiayang He ◽  
Elena Austin ◽  
Edmund Seto ◽  
Igor Novosselov
Keyword(s):  
Source Monitoring ◽  
Particle Density ◽  
Low Cost ◽  
Complex Refractive Index ◽  
Environmental Parameters ◽  
Number Concentration ◽  
Index Of Refraction ◽  
Sensor Data ◽  
Particle Count ◽  
Mass Concentrations

Low-cost optical scattering particulate matter (PM) sensors report total or size-specific particle counts and mass concentrations. The PM concentration and size are estimated by the original equipment manufacturer (OEM) proprietary algorithms, which have inherent limitations since particle scattering depends on particles’ properties such as size, shape, and complex index of refraction (CRI) as well as environmental parameters such as temperature and relative humidity (RH). As low-cost PM sensors are not able to resolve individual particles, there is a need to characterize and calibrate sensors’ performance under a controlled environment. Here, we present improved calibration algorithms for Plantower PMS A003 sensor for mass indices and size-resolved number concentration. An aerosol chamber experimental protocol was used to evaluate sensor-to-sensor data reproducibility. The calibration was performed using four polydisperse test aerosols. The particle size distribution OEM calibration for PMS A003 sensor did not agree with the reference single particle sizer measurements. For the number concentration calibration, the linear model without adjusting for the aerosol properties and environmental conditions yields an absolute error (NMAE) of ~ 4.0% compared to the reference instrument. The calibration models adjusted for particle CRI and density account for non-linearity in the OEM’s mass concentrations estimates with NMAE within 5.0%. The calibration algorithms developed in this study can be used in indoor air quality monitoring, occupational/industrial exposure assessments, or near-source monitoring scenarios where field calibration might be challenging.

scholarly journals Toward Near Real-Time Kinematics Differential Correction: In View of Geometrically Augmented Sensor Data for Mobile Microclimate Monitoring

2020 ◽  
Vol 2 (1) ◽  
pp. 61
Author(s):  
Stefano Tondini ◽  
Farshad Hasanabadi ◽  
Roberto Monsorno ◽  
Antonio Novelli
Keyword(s):  
Urban Communities ◽  
Urban Areas ◽  
Global Climate ◽  
Low Cost ◽  
Life Quality ◽  
Environmental Parameters ◽  
Mitigation Strategies ◽  
Added Value ◽  
Sensor Data ◽  
Urban Context

In the scenario of massive urbanization and global climate change, the acquisition of microclimatic data in urban areas plays a key role in responsive adaptation and mitigation strategies. The enrichment of kinematic sensor data with precise, high-frequency and robust positioning directly relates to the possibility of creating added-value services devoted to improving the life-quality of urban communities. This work presents a low-cost cloud-connected mobile monitoring platform for multiple environmental parameters and their spatial variation in the urban context.

scholarly journals Low-Cost IoT Enabled Embedded System for Measurement of Environmental Pollutants

2021 ◽  
Vol 20 (4) ◽  
Author(s):  
C. Mani Kumar ◽  
Shahid Ali ◽  
P. Sri Lakshmi ◽  
G. Raja Kullayappa ◽  
K. Tanveer Alam
Keyword(s):  
Embedded System ◽  
High Speed ◽  
Low Cost ◽  
Environmental Pollutants ◽  
Environmental Parameters ◽  
Sensor Data ◽  
User Friendliness ◽  
Meteorological Systems ◽  
Conventional Systems ◽  
Physical Quantities

In today’s world, with ever-changing pollutants and their concentrations, the designing of low-cost meteorological systems is unavoidable for assessing environmental parameters. Wireless instrumentation is an effective way of measuring the physical quantities as it can measure and transmit the data to the targeted location at high speed. In the present work, an IoT-enabled embedded system was developed to measure the concentration of carbon dioxide, ozone, and the presence of smoke. The ARM microcontroller reads the sensor data and processes the information to calculate the pollutant parameters. The measured data is displayed on the LCD, mobile phone, and a computer simultaneously using wireless technology. With Embedded C, the Keil compiler was used to develop the interfacing software for the designed system. Portability, user-friendliness, and reliability are the significant advantages of the device compared with the conventional systems, and it can be widely used as an inexpensive solution for the monitoring of environmental conditions.

scholarly journals Proteus II: Design and Evaluation of an Integrated Power-Efficient Underwater Sensor Node

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Wouter A. P. van Kleunen ◽  
Niels A. Moseley ◽  
Paul J. M. Havinga ◽  
Nirvana Meratnia
Keyword(s):  
Sensor Node ◽  
Low Cost ◽  
Environmental Parameters ◽  
Sensor Data ◽  
Modulation Scheme ◽  
Time Of Arrival ◽  
Analog To Digital ◽  
Power Efficient ◽  
Toa Estimation ◽  
And Performance

We describe the design and evaluation of an integrated low-cost underwater sensor node designed for reconfigurability, allowing continuous operation on a relatively small rechargeable battery for one month. The node uses a host CPU for the network protocols and processing sensor data and a separate CPU performs signal processing for the ultrasonic acoustic software-defined Modulator/Demodulator (MODEM). A Frequency Shift Keying- (FSK-) based modulation scheme with configurable symbol rates, Hamming error correction, and Time-of-Arrival (ToA) estimation for underwater positioning is implemented. The onboard sensors, an accelerometer and a temperature sensor, can be used to measure basic environmental parameters; additional internal and external sensors are supported through industry-standard interfaces (I2C, SPI, and RS232) and an Analog to Digital Converter (ADC) for analog peripherals. A 433 MHz radio can be used when the node is deployed at the surface. Tests were performed to validate the low-power operation. Moreover the acoustic communication range and performance and ToA capabilities were evaluated. Results show that the node achieves the one-month lifetime, is able to perform communication in highly reflective environments, and performs ToA estimation with an accuracy of about 1-2 meters.

scholarly journals Implementation of a Six-Layer Smart Factory Architecture with Special Focus on Transdisciplinary Engineering Education

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2944
Author(s):  
Benjamin James Ralph ◽  
Marcel Sorger ◽  
Benjamin Schödinger ◽  
Hans-Jörg Schmölzer ◽  
Karin Hartl ◽  
...  
Keyword(s):  
Open Source ◽  
User Interfaces ◽  
Industrial Revolution ◽  
Low Cost ◽  
Material Behavior ◽  
Sensor Data ◽  
Management Tool ◽  
Special Focus ◽  
Programming Environments ◽  
Metal Processing

Smart factories are an integral element of the manufacturing infrastructure in the context of the fourth industrial revolution. Nevertheless, there is frequently a deficiency of adequate training facilities for future engineering experts in the academic environment. For this reason, this paper describes the development and implementation of two different layer architectures for the metal processing environment. The first architecture is based on low-cost but resilient devices, allowing interested parties to work with mostly open-source interfaces and standard back-end programming environments. Additionally, one proprietary and two open-source graphical user interfaces (GUIs) were developed. Those interfaces can be adapted front-end as well as back-end, ensuring a holistic comprehension of their capabilities and limits. As a result, a six-layer architecture, from digitization to an interactive project management tool, was designed and implemented in the practical workflow at the academic institution. To take the complexity of thermo-mechanical processing in the metal processing field into account, an alternative layer, connected with the thermo-mechanical treatment simulator Gleeble 3800, was designed. This framework is capable of transferring sensor data with high frequency, enabling data collection for the numerical simulation of complex material behavior under high temperature processing. Finally, the possibility of connecting both systems by using open-source software packages is demonstrated.

scholarly journals Development and Evaluation of a Low-Drift Inertial Sensor-Based System for Analysis of Alpine Skiing Performance

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2480
Author(s):  
Isidoro Ruiz-García ◽  
Ismael Navarro-Marchal ◽  
Javier Ocaña-Wilhelmi ◽  
Alberto J. Palma ◽  
Pablo J. Gómez-López ◽  
...  
Keyword(s):  
Data Fusion ◽  
Reference System ◽  
Inertial Sensor ◽  
Low Cost ◽  
Sampling Rate ◽  
Sensor Data ◽  
Fusion Algorithm ◽  
Improve Technique ◽  
Worst Case ◽  
Sensor Data Fusion

In skiing it is important to know how the skier accelerates and inclines the skis during the turn to avoid injuries and improve technique. The purpose of this pilot study with three participants was to develop and evaluate a compact, wireless, and low-cost system for detecting the inclination and acceleration of skis in the field based on inertial measurement units (IMU). To that end, a commercial IMU board was placed on each ski behind the skier boot. With the use of an attitude and heading reference system algorithm included in the sensor board, the orientation and attitude data of the skis were obtained (roll, pitch, and yaw) by IMU sensor data fusion. Results demonstrate that the proposed IMU-based system can provide reliable low-drifted data up to 11 min of continuous usage in the worst case. Inertial angle data from the IMU-based system were compared with the data collected by a video-based 3D-kinematic reference system to evaluate its operation in terms of data correlation and system performance. Correlation coefficients between 0.889 (roll) and 0.991 (yaw) were obtained. Mean biases from −1.13° (roll) to 0.44° (yaw) and 95% limits of agreements from 2.87° (yaw) to 6.27° (roll) were calculated for the 1-min trials. Although low mean biases were achieved, some limitations arose in the system precision for pitch and roll estimations that could be due to the low sampling rate allowed by the sensor data fusion algorithm and the initial zeroing of the gyroscope.

scholarly journals Turning Base Transceiver Stations into Scalable and Controllable DC Microgrids Based on a Smart Sensing Strategy

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1202
Author(s):  
Miguel Tradacete ◽  
Carlos Santos ◽  
José A. Jiménez ◽  
Fco Javier Rodríguez ◽  
Pedro Martín ◽  
...  
Keyword(s):  
Electricity Market ◽  
Low Cost ◽  
Storage System ◽  
Environmental Parameters ◽  
Weather Conditions ◽  
Energy Storage System ◽  
Electricity Grid ◽  
Dc Microgrids ◽  
Smart Sensing ◽  
Battery Energy

This paper describes a practical approach to the transformation of Base Transceiver Stations (BTSs) into scalable and controllable DC Microgrids in which an energy management system (EMS) is developed to maximize the economic benefit. The EMS strategy focuses on efficiently managing a Battery Energy Storage System (BESS) along with photovoltaic (PV) energy generation, and non-critical load-shedding. The EMS collects data such as real-time energy consumption and generation, and environmental parameters such as temperature, wind speed and irradiance, using a smart sensing strategy whereby measurements can be recorded and computing can be performed both locally and in the cloud. Within the Spanish electricity market and applying a two-tariff pricing, annual savings per installed battery power of 16.8 euros/kW are achieved. The system has the advantage that it can be applied to both new and existing installations, providing a two-way connection to the electricity grid, PV generation, smart measurement systems and the necessary management software. All these functions are integrated in a flexible and low cost HW/SW architecture. Finally, the whole system is validated through real tests carried out on a pilot plant and under different weather conditions.

scholarly journals BIM and IoT Sensors Integration: A Framework for Consumption and Indoor Conditions Data Monitoring of Existing Buildings

2021 ◽  
Vol 13 (8) ◽  
pp. 4496
Author(s):  
Giuseppe Desogus ◽  
Emanuela Quaquero ◽  
Giulia Rubiu ◽  
Gianluca Gatto ◽  
Cristian Perra
Keyword(s):  
Energy Consumption ◽  
Low Cost ◽  
Application Programming Interface ◽  
Visual Programming ◽  
Information Modeling ◽  
Sensor Data ◽  
Time Data ◽  
Existing Building ◽  
Building Maintenance ◽  
Indoor Conditions

The low accessibility to the information regarding buildings current performances causes deep difficulties in planning appropriate interventions. Internet of Things (IoT) sensors make available a high quantity of data on energy consumptions and indoor conditions of an existing building that can drive the choice of energy retrofit interventions. Moreover, the current developments in the topic of the digital twin are leading the diffusion of Building Information Modeling (BIM) methods and tools that can provide valid support to manage all data and information for the retrofit process. This paper shows the aim and the findings of research focused on testing the integrated use of BIM methodology and IoT systems. A common data platform for the visualization of building indoor conditions (e.g., temperature, luminance etc.) and of energy consumption parameters was carried out. This platform, tested on a case study located in Italy, is developed with the integration of low-cost IoT sensors and the Revit model. To obtain a dynamic and automated exchange of data between the sensors and the BIM model, the Revit software was integrated with the Dynamo visual programming platform and with a specific Application Programming Interface (API). It is an easy and straightforward tool that can provide building managers with real-time data and information about the energy consumption and the indoor conditions of buildings, but also allows for viewing of the historical sensor data table and creating graphical historical sensor data. Furthermore, the BIM model allows the management of other useful information about the building, such as dimensional data, functions, characteristics of the components of the building, maintenance status etc., which are essential for a much more conscious, effective and accurate management of the building and for defining the most suitable retrofit scenarios.

scholarly journals 3D Affine: An Embedding of Local Image Features for Viewpoint Invariance Using RGB-D Sensor Data

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 291 ◽  
Author(s):  
Hamdi Sahloul ◽  
Shouhei Shirafuji ◽  
Jun Ota
Keyword(s):  
Low Cost ◽  
Image Features ◽  
Image Feature ◽  
Sensor Data ◽  
Invariant Representation ◽  
Depth Sensors ◽  
Viewpoint Invariance ◽  
Surface Discontinuities ◽  
Local Image ◽  
Local Image Features

Local image features are invariant to in-plane rotations and robust to minor viewpoint changes. However, the current detectors and descriptors for local image features fail to accommodate out-of-plane rotations larger than 25°–30°. Invariance to such viewpoint changes is essential for numerous applications, including wide baseline matching, 6D pose estimation, and object reconstruction. In this study, we present a general embedding that wraps a detector/descriptor pair in order to increase viewpoint invariance by exploiting input depth maps. The proposed embedding locates smooth surfaces within the input RGB-D images and projects them into a viewpoint invariant representation, enabling the detection and description of more viewpoint invariant features. Our embedding can be utilized with different combinations of descriptor/detector pairs, according to the desired application. Using synthetic and real-world objects, we evaluated the viewpoint invariance of various detectors and descriptors, for both standalone and embedded approaches. While standalone local image features fail to accommodate average viewpoint changes beyond 33.3°, our proposed embedding boosted the viewpoint invariance to different levels, depending on the scene geometry. Objects with distinct surface discontinuities were on average invariant up to 52.8°, and the overall average for all evaluated datasets was 45.4°. Similarly, out of a total of 140 combinations involving 20 local image features and various objects with distinct surface discontinuities, only a single standalone local image feature exceeded the goal of 60° viewpoint difference in just two combinations, as compared with 19 different local image features succeeding in 73 combinations when wrapped in the proposed embedding. Furthermore, the proposed approach operates robustly in the presence of input depth noise, even that of low-cost commodity depth sensors, and well beyond.

Based on FPGA Intelligent Physiological Parameters Acquisition

2013 ◽  
Vol 344 ◽  
pp. 107-110
Author(s):  
Shun Ren Hu ◽  
Ya Chen Gan ◽  
Ming Bao ◽  
Jing Wei Wang
Keyword(s):  
High Speed ◽  
Low Cost ◽  
Physiological Parameters ◽  
Sensor Data ◽  
Low Power Consumption ◽  
Physiological Signal ◽  
Pulse Sensor ◽  
Monitoring Applications ◽  
Field Programmable ◽  
Design Ideas

For the physiological signal monitoring applications, as a micro-controller based on field programmable gate array (FPGA) physiological parameters intelligent acquisition system is given, which has the advantages of low cost, high speed, low power consumption. FPGA is responsible for the completion of pulse sensor, the temperature sensor, acceleration sensor data acquisition and serial output and so on. Focuses on the design ideas and architecture of the various subsystems of the whole system, gives the internal FPGA circuit diagram of the entire system. The whole system is easy to implement and has a very good promotional value.

Low Cost Sensor Data Fusion in Omnidirectional Mobile Robot Feedback System to Improve the Navigation Accuracy

2014 ◽  
Vol 607 ◽  
pp. 791-794 ◽  
Author(s):  
Wei Kang Tey ◽  
Che Fai Yeong ◽  
Yip Loon Seow ◽  
Eileen Lee Ming Su ◽  
Swee Ho Tang
Keyword(s):  
Mobile Robot ◽  
Sensor Fusion ◽  
Low Cost ◽  
Feedback System ◽  
Sensor Data ◽  
Research Setting ◽  
Fusion Technique ◽  
Omnidirectional Mobile Robot ◽  
The Cost ◽  
Navigation Accuracy

Omnidirectional mobile robot has gained popularity among researchers. However, omnidirectional mobile robot is rarely been applied in industry field especially in the factory which is relatively more dynamic than normal research setting condition. Hence, it is very important to have a stable yet reliable feedback system to allow a more efficient and better performance controller on the robot. In order to ensure the reliability of the robot, many of the researchers use high cost solution in the feedback of the robot. For example, there are researchers use global camera as feedback. This solution has increases the cost of the robot setup fee to a relatively high amount. The setup system is also hard to modify and lack of flexibility. In this paper, a novel sensor fusion technique is proposed and the result is discussed.

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