scholarly journals Sensing the Environmental Neighborhoods

2021 ◽  
pp. 124-133
Author(s):  
Maider Llaguno-Munitxa ◽  
Elie Bou-Zeid
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Low Cost ◽  
Fast Response ◽  
Environmental Data ◽  
Design Strategies ◽  
Policy Makers ◽  
Princeton University ◽  
Sensing Technology ◽  
Neighborhood Scale

AbstractGiven the benefits of fine mapping of large urban areas affordably, mobile environmental sensing technologies are becoming increasingly popular to complement the traditional stationary weather and air quality sensing stations. However the reliability and accuracy of low-cost mobile urban technologies is often questioned. This paper presents the design of a fast-response, autonomous and affordable Mobile Urban Sensing Technology (MUST) for the acquisition of high spatial resolution environmental data. Only when accurate neighborhood scale environmental data is affordable and accessible for architects, urban planners and policy makers, can design strategies to enhance urban health be effectively implemented. The results of an experimental air quality sensing campaign developed within Princeton University Campus is presented.

scholarly journals REAL-TIME ENVIRONMENTAL SENSORS TO IMPROVE HEALTH IN THE SENSING CITY

2016 ◽  
Vol XLI-B2 ◽  
pp. 729-733 ◽  
Author(s):  
L. Marek ◽  
M. Campbell ◽  
M. Epton ◽  
M. Storer ◽  
S. Kingham
Keyword(s):  
Quality Of Life ◽  
Air Pollution ◽  
Air Quality ◽  
Real Time ◽  
Low Cost ◽  
Monitoring Network ◽  
Environmental Data ◽  
Chronic Obstructive ◽  
Actual Usage

The opportunity of an emerging smart city in post-disaster Christchurch has been explored as a way to improve the quality of life of people suffering Chronic Obstructive Pulmonary Disease (COPD), which is a progressive disease that affects respiratory function. It affects 1 in 15 New Zealanders and is the 4th largest cause of death, with significant costs to the health system. While, cigarette smoking is the leading cause of COPD, long-term exposure to other lung irritants, such as air pollution, chemical fumes, or dust can also cause and exacerbate it. Currently, we do know little what happens to the patients with COPD after they leave a doctor’s care. By learning more about patients’ movements in space and time, we can better understand the impacts of both the environment and personal mobility on the disease. This research is studying patients with COPD by using GPS-enabled smartphones, combined with the data about their spatiotemporal movements and information about their actual usage of medication in near real-time. We measure environmental data in the city, including air pollution, humidity and temperature and how this may subsequently be associated with COPD symptoms. In addition to the existing air quality monitoring network, to improve the spatial scale of our analysis, we deployed a series of low-cost Internet of Things (IoT) air quality sensors as well. The study demonstrates how health devices, smartphones and IoT sensors are becoming a part of a new health data ecosystem and how their usage could provide information about high-risk health hotspots, which, in the longer term, could lead to improvement in the quality of life for patients with COPD.

scholarly journals A Review of Carbon Nanotubes-Based Gas Sensors

2009 ◽  
Vol 2009 ◽  
pp. 1-24 ◽  
Author(s):  
Yun Wang ◽  
John T. W. Yeow
Keyword(s):  
Carbon Nanotubes ◽  
Gas Sensors ◽  
Gas Sensing ◽  
Low Cost ◽  
High Surface ◽  
Hollow Structure ◽  
Volume Ratio ◽  
Fast Response ◽  
Sensing Technology ◽  
Structure Of Nanomaterials

Gas sensors have attracted intensive research interest due to the demand of sensitive, fast response, and stable sensors for industry, environmental monitoring, biomedicine, and so forth. The development of nanotechnology has created huge potential to build highly sensitive, low cost, portable sensors with low power consumption. The extremely high surface-to-volume ratio and hollow structure of nanomaterials is ideal for the adsorption of gas molecules. Particularly, the advent of carbon nanotubes (CNTs) has fuelled the inventions of gas sensors that exploit CNTs' unique geometry, morphology, and material properties. Upon exposure to certain gases, the changes in CNTs' properties can be detected by various methods. Therefore, CNTs-based gas sensors and their mechanisms have been widely studied recently. In this paper, a broad but yet in-depth survey of current CNTs-based gas sensing technology is presented. Both experimental works and theoretical simulations are reviewed. The design, fabrication, and the sensing mechanisms of the CNTs-based gas sensors are discussed. The challenges and perspectives of the research are also addressed in this review.

scholarly journals A Low-Cost Sensing System for Cooperative Air Quality Monitoring in Urban Areas

Sensors ◽  
2015 ◽  
Vol 15 (6) ◽  
pp. 12242-12259 ◽  
Author(s):  
Simone Brienza ◽  
Andrea Galli ◽  
Giuseppe Anastasi ◽  
Paolo Bruschi
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Low Cost ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Sensing System

Research on Digital Substation IOT Based on SAW Sensing Technology

2015 ◽  
Vol 738-739 ◽  
pp. 125-128 ◽  
Author(s):  
Da Wei Lv ◽  
Xiao Juan Li ◽  
Li Xin Yang ◽  
Dian Jun Liu ◽  
Kui Xiong ◽  
...  
Keyword(s):  
High Temperature ◽  
Internet Of Things ◽  
Electromagnetic Radiation ◽  
Low Cost ◽  
Fast Response ◽  
Harsh Environments ◽  
Sensing Technology ◽  
Digital Substation ◽  
Almost All ◽  
Rotating Objects

SAW sensing technology has advantages of wireless, passive, small size, low cost, fast response, strong anti-electromagnetic radiation, measurable for moving or rotating objects, tolerable for wet dirty or high temperature and other harsh environments. Comparing with the traditional sensing methods, the test of SAW sensing technology can cover almost all the needs of digital substation internet of things.

Characterization of Ambient Air Quality in Selected Urban Areas in Uganda: A Low-Cost Approach

2021 ◽  
Author(s):  
Deo Okure ◽  
Engineer Bainomugisha ◽  
Nancy Lozano-Gracia ◽  
Maria Edisa Soppelsa
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Low Cost ◽  
Ambient Air ◽  
Ambient Air Quality ◽  
Cost Approach

Assessment of heterogenity of air pollution within an urban canopy

2020 ◽  
Author(s):  
Vivien Voss ◽  
K. Heinke Schlünzen ◽  
David Grawe
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Citizen Science ◽  
Urban Areas ◽  
Hot Spot ◽  
Low Cost ◽  
Urban Canopy ◽  
Limit Values ◽  
Data Standard ◽  
The City

<p>Air pollution is an important topic within urban areas.  Limit values as given in the European Guidelines are introduced to reduce negative effects on humans and vegetation.  Exceedances of the limit values are to be assessed using measurements.  In case of found exceedances of the limit values, the local authorities need to act to reduce pollution levels. Highest values are found for several pollutants (NOx, NO2, particles) within densely build-up urban areas with traffic emissions being the major source and dispersion being very much impacted by the urban structures.  The quality assured measuring network used by the authorities is often too coarse to determine the heterogeneity in the concentration field. Low cost sample devices as employed in several citizen science projects might help to overcome the data sparsity. Volunteers measure the air quality at many sites, contribute to the measurement networks and provide the data on the web. However, the questions arising are: a) Are these data of sufficient high quality to provide results comparable to those of the quality assured networks? b) Is the network density sufficient to determine concentration patterns within the urban canopy layer? <br>One-year data from a citizen science network, which measures particulate matter (PM10, PM2.5) were compared to measurements provided by the local environmental agency, using two hot-spot areas in the city of Hamburg as an example. To determine how well the measurements agree with each other, a regression analyses was performed dependent on seasonal and diurnal cycles. Additionally, model simulations with the microscale obstacle resolving model MITRAS were performed for two characteristic building structures and different meteorological situations. The model results were used to determine local hot spots as well as areas where measurements might represent the concentration of particles for the urban quarter. The low cost sensor measurements show a general agreement to the city’s measurements, however, the values per sensor differ. Moreover, the measurements of the low-cost-sensor show an unrealistic dependence on relative humidity, resulting in over- or underestimations in certain cases. The model results clearly show that only a few sites allow measurements to be representative for a city quarter. The measurements of the citizen science project can provide a good overview about the tendencies of the air quality, but are currently not of sufficient quality to provide measurements calling for legal action.</p><p>The model results were used for the project AtMoDat. AtMoDat is an attempt to create a data standard for obstacle resolving models based on the existing Climate and Forecast (CF) conventions. A web-based survey is developed to get information on the requirements for the data standard. The next step is to extend the collection of model characteristics and eventually to provide a generic scheme.</p><p><strong>Acknowledgements</strong><br>This work contributes to project “AtMoDat” funded by the Federal Ministry of Education and Research under the funding number 16QK02C. Responsibility for the content of this publication lies with the authors.</p>

scholarly journals Application of a Machine Learning Methodology for Data Implementation

2020 ◽  
Vol 4 (1) ◽  
pp. 11
Author(s):  
Chris G. Tzanis ◽  
Anastasios Alimissis ◽  
Ioannis Koutsogiannis
Keyword(s):  
Machine Learning ◽  
Air Quality ◽  
Urban Areas ◽  
Spatial Interpolation ◽  
Missing Values ◽  
Ambient Air ◽  
Monitoring Networks ◽  
Policy Makers ◽  
Environmental Statistics ◽  
Quality Maps

An important aspect in environmental sciences is the study of air quality, using statistical methods (environmental statistics) which utilize large datasets of climatic parameters. The air quality monitoring networks that operate in urban areas provide data on the most important pollutants, which via environmental statistics can be used for the development of continuous surfaces of pollutants’ concentrations. Generating ambient air quality maps can help guide policy makers and researchers to formulate measures to minimize the adverse effects. The information needed for a mapping application can be obtained by employing spatial interpolation methods to the available data, for generating estimations of air quality distributions. This study used point monitoring data from the network of stations that operates in Athens. A machine learning scheme was applied as a method to spatially estimate pollutants’ concentrations and the results could be effectively used to implement missing values and provide representative data for statistical analyses purposes.

scholarly journals A compact, modular and low-cost Internet of Things (IoT) platform for air quality monitoring in urban areas

2020 ◽  
Vol 1710 ◽  
pp. 012004
Author(s):  
Christos Spandonidis ◽  
Stefanos Tsantilas ◽  
Elias Sedikos ◽  
Nektarios Galiatsatos ◽  
Fotios Giannopoulos ◽  
...  
Keyword(s):  
Air Quality ◽  
Internet Of Things ◽  
Urban Areas ◽  
Low Cost ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Iot Platform

scholarly journals Measure particulate matter by yourself: data-quality monitoring in a citizen science project

2019 ◽  
Vol 8 (2) ◽  
pp. 317-328 ◽  
Author(s):  
Aboubakr Benabbas ◽  
Martin Geißelbrecht ◽  
Gabriel Martin Nikol ◽  
Lukas Mahr ◽  
Daniel Nähr ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Data Quality ◽  
Urban Areas ◽  
Low Cost ◽  
Quality Monitoring ◽  
Sensor Data ◽  
And Control ◽  
Future Work ◽  
The Impact

Abstract. The concern about air quality in urban areas and the impact of particulate matter (PM) on public health is turning into a big debate. A good solution to sensitize people to this issue is to involve them in the process of air quality monitoring. This paper presents contributions in the field of PM measurements using low-cost sensors. We show how a low-cost PM sensor can be extended to transfer data not only over Wi-Fi but also over the LoRa protocol. Then, we identify some of the correlations existing in the data through data analysis. Afterwards, we show how semantic technologies can help model and control sensor data quality in an increasing PM sensor network. We finally wrap up with a conclusion and plans for future work.

Control Design Strategies for Semi-Active Suspension System

2019 ◽  
Author(s):  
Jessica Gissella Maradey Lazaro ◽  
Helio Esteban Villegas ◽  
Brajan Ruiz ◽  
Andrés Aldana
Keyword(s):  
Control Strategies ◽  
Low Cost ◽  
Active Suspension ◽  
Fast Response ◽  
Suspension System ◽  
Operating Conditions ◽  
Mathematical Treatment ◽  
Design Strategies ◽  
Control Laws ◽  
And Performance

Abstract Semi-Active Suspension Systems are very important to achieve comfort, ride handling, ground contact of the tyre, road-friendliness and works in a large range of operation. Its use an active dampers and the action of control is very good because of low energy consumption. The force of the damper is regulated according to the operating conditions. Magnetorheological Dampers are commonly used because of his yield resistance, low power, fast response and low cost of production. However, they behave in a non-linear way, following a dynamic of hysteresis so you should give a more sophisticated mathematical treatment. In this paper, we describe the modelling and design of two control strategies for Semi-Active Suspension System. Two control laws will be developed; classical PID and Fuzzy Logic controls law with the simulation and evaluate the stability and performance properties of our controllers in several different scenarios through analysis and simulation simultaneously. The performance of the system is determined by computer simulation in Matlab/ Simulink. The results obtained to compare and prove the effectiveness of these control approaches.

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