Environmental Data Collection Research Articles

Public Participation in Air Sampling and Water Quality Test Kit Development to Enable Citizen Science.

Public participation in environmental data collection is a rapidly growing approach providing opportunity for hands-on public engagement in environmental field studies. This methodology is important when addressing community-identified exposure concerns. Our goal was to establish an academic-community partnership between University of Cincinnati (UC) researchers and local officials and residents of Guernsey County, Ohio, to address their interest in assessing environmental quality near proposed and operating natural gas extraction (NGE) waste sites. A pilot research study was developed using community-based participatory research principles. A community resident was trained to collect air samples. Air was sampled at 10 locations for 63 volatile organic compounds (VOCs). Water quality test kits were developed in partnership with local middle and high school teachers. Community partners were involved throughout the project. VOCs were detected at all locations. Nineteen unique VOCs were detected; one was above the recommended exposure level. Findings were reported back to local officials and community members. Water quality test kits were developed and then piloted in middle school and high school classrooms. Academic-community partnerships were instrumental in the identification of sampling locations, obtaining the participation of landowners, and conducting sampling. Measuring the impact of NGE activities on air quality is challenging owing to competing exposures, limited resources, and access to sites. Water quality test kits were found by Guernsey County teachers to be useful tools in the classroom.

A probabilistic multivariate copula-based technique for faulty node diagnosis in wireless sensor networks

Wireless sensor networks (WSNs) find extensive applications in various sensitive domains such as tracking, monitoring, environmental data collection and border surveillance. In these cases, the collected data are considered as a critical resource and used to detect any anomalies or abnormal behavior, providing information about an occurring event or a node failure. An outlier detection process must be set up to ensure the proper functioning of the monitoring system. The existing approaches are limited by assumptions on a specific distribution or a predefined data range of the collected data. Often these assumptions do not hold in practice, the data distribution is not known or determining reliable upper and lower bounds for the set of data is not possible. To overcome this, we propose a new copula-based probabilistic multivariate outlier detection method for faulty node detection in wireless sensor networks (WSNs). The joint probability density function of the copula is constructed considering dependency among the captured n−sensed measures without making any assumptions on the distribution of the collected data. The samples having probabilities violating a predetermined control limit are classified to be faulty. The performance of the proposed technique is observed to be better than the existing statistical methods.

Open-Source Implementation of an Integrated, Low-Cost Environmental Monitoring System (EMS) for developing countries

Whilst widely accepted as an important facet of Open Source technologies and their application, the scientific evaluation of such technologies and systems is often underexplored in research. This work presents an integrated approach of developing a proto-type Environmental Monitoring System (EMS) based on open source hardware & software, and the system’s reliability in terms of data accuracy. The system is able to measure nine environmental parameters: rainfall, temperature, barometric pressure, humidity, wind speed, wind direction, solar radiation, soil moisture and water level. Opposing to sophisticated and conventional environmental data collection systems such as automatic and manual weather stations belong to Meteorological and Irrigation department of Sri Lanka, this research has shown a promising way of establishing a dense coverage to monitor the environmental phenomena in a more cost effective manner.

Data challenges and opportunities for environmental management of North Sea oil and gas decommissioning in an era of blue growth

Maritime industries routinely collect critical environmental data needed for sustainable management of marine ecosystems, supporting both the blue economy and future growth. Collating this information would provide a valuable resource for all stakeholders. For the North Sea, the oil and gas industry has been a dominant presence for over 50 years that has contributed to a wealth of knowledge about the environment. As the industry begins to decommission its offshore structures, this information will be critical for avoiding duplication of effort in data collection and ensuring best environmental management of offshore activities. This paper summarises the outcomes of a Blue Growth Data Challenge Workshop held in 2017 with participants from: the oil and gas industry; the key UK regulatory and management bodies for oil and gas decommissioning; open access data facilitators; and academic and research institutes. Here, environmental data collection and archiving by oil and gas operators in the North Sea are described, alongside how this compares to other offshore industries; what the barriers and opportunities surrounding environmental data sharing are; and how wider data sharing from offshore industries could be achieved. Five primary barriers to data sharing were identified: 1) Incentives, 2) Risk Perception, 3) Working Cultures, 4) Financial Models, and 5) Data Ownership. Active and transparent communication and collaboration between stakeholders including industry, regulatory bodies, data portals and academic institutions will be key to unlocking the data that will be critical to informing responsible decommissioning decisions for offshore oil and gas structures in the North Sea.

A novel method of combined interval analysis and homotopy continuation in indoor building reconstruction

ABSTRACTIn this article, several mathematical and statistical methods for uncertainty modelling in indoor buildings are investigated. To reduce the time and cost of the indoor building data-acquisition process, the Trimble LaserAce 1000 rangefinder is used. The accuracy of the rangefinder is evaluated and a simple spatial model is reconstructed. The rangefinder has been used for forest applications to measure the height of trees. In this article, the rangefinder is used for indoor building environment data collection and mapping. The rangefinder was calibrated using a least squares adjustment algorithm and a novel method of interval-valued homotopy as a continuous deformation that reconstructs straight lines or algebraic curves between any pair of three-dimensional data. Homotopy gives better results in term of root mean square error than conventional surveying engineering methods where, in some cases, cubic homotopy gives results 11 times better than conventional methods.

Using a One Health Approach to Build an Integrated Surveillance Data System

Objective: Integrate and streamline the collection and analysis of environmental, veterinary, and vector zoonotic data using a One Health approach to data system development.Introduction: Environmental Public Health Zoonotic Disease surveillance includes veternary, environmental, and vector data. Surveillance systems within each sector may appear disparate from each other, although they are actually complimentaly and closely allied. Consolidating and integrating data in to one application can be challenging, but there are commonalities shared by all. The goal of the One Health Integrated Data Sysytem is to standardize data collection, streamline data entry, and integrate these sectors in to one application.Methods: Data Assessment. An assessment of each surveillance function was carried out to evaluate data types and needs.Identify Commonalities. Common data was identified across each of the surveillance areas.Identify Unique Data. Data unique to specific surveillance efforts was identified.Build Data Structure. A back-end data structure was developed that reflected the data needs from each surveillance area.Build Data Entry Interfaces. Data entry interfaces were developed to meet the needs of each surveillance area.Build Data QC. Procedures were developed that run several quality control checks on the data.Build Data Eports. To allow users to carry out more extensive analysis of data, customized data exports were built.Results: This data integration project resulted in:● Reduced time spent entering and managing data● Improved data entry error rates● Increased visibility through automated program metrics● Improved access to data from data usersConclusions: Integrating data and building a data system that reflects the diversity of environmental, veterinary, and vector surveillance data is doable using off-the-shelf database tools. The process of integrating data and building the data structure results in a more intimate understanding of the data revealing opportunities for improving data quality.

Measuring high-density built environment for public health research: Uncertainty with respect to data, indicator design and spatial scale.

Uncertainty with respect to built environment (BE) data collection, measure conceptualization and spatial scales is evident in urban health research, but most findings are from relatively lowdensity contexts. We selected Hong Kong, an iconic high-density city, as the study area as limited research has been conducted on uncertainty in such areas. We used geocoded home addresses (n=5732) from a large population-based cohort in Hong Kong to extract BE measures for the participants' place of residence based on an internationally recognized BE framework. Variability of the measures was mapped and Spearman's rank correlation calculated to assess how well the relationships among indicators are preserved across variables and spatial scales. We found extreme variations and uncertainties for the 180 measures collected using comprehensive data and advanced geographic information systems modelling techniques. We highlight the implications of methodological selection and spatial scales of the measures. The results suggest that more robust information regarding urban health research in high-density city would emerge if greater consideration were given to BE data, design methods and spatial scales of the BE measures.

Multi-Source Energy Harvesting and Storage for Floating Wireless Sensor Network Nodes With Long Range Communication Capability

Wireless sensor networks are widely used for environmental monitoring in remote areas. They are mainly composed of wireless sensor nodes, usually powered by batteries with limited capacity, but are expected to communicate in long range and operate for extended time periods. To overcome these limitations, many energy harvesting techniques are proposed to power wireless nodes for prolonged operation, whereas multihop techniques are utilized to extend the communication range. In this paper, a novel floating device with multisource energy harvesting technology that can be used as a wireless sensor node is proposed. The long range communication between wireless sensor nodes and a gateway is established through LoRa technology. In addition to conventional solar panels, an energy harvesting technique based on thermoelectric generators exploiting thermal differences created between water surface and materials exposed to sunlight is proposed. Energy generated from photovoltaic and thermoelectric generators is combined to power the wireless sensor node. This floating device consumes 6.6216 Wh per day when used as a wireless sensor node for the collection and transmission of environmental data. The sensor node can operate on a water surface for at least 9.6 days when it is not exposed to sunlight. During a sunny day, the floating device can harvest 8.375 Wh from solar panels and 0.425 Wh from thermoelectric generation. In other words, the floating device harvests sufficient energy to be self-sustaining during sunny days.

Environmental and health data needed to develop national surveillance systems in industrially contaminated sites.

this paper is based upon work from COST Action ICSHNet. Public health surveillance (PHS) of industrially contaminated sites (ICSs) is likely to play a role in supporting the monitoring of harmful aspects of ICSs and related interventions. Environmental public health tracking (EPHT) has been proposed and developed as an approach to PHS when environmental factors affecting health are involved. to identify existing arrangements for continuous collection and analysis of environmental and health data to guide the development of an optimal EPHT approach which would support the characterization of the impact on health of ICS. a literature search was conducted in PubMed following a structured approach to identify methodological aspects relevant to surveillance of ICSs. In addition, eight further studies on this topic, mainly from three European Countries (Spain, Italy, and France), were included by the research team. the identified 17 examples of surveillance studies include a heterogeneous variety of industrial activities, covering from cross-national to local scenarios. Continuous monitoring systems for gathering environmental data related to ICSs were used only in two cases; a qualitative approach and/or punctual sampling for soil, air, and water of local foodstuff took place in the rest. Exposure assessment was conducted according to four main methods: qualitative definition for the presence/absence of a source, distance to a source, dispersion modelling, and biomonitoring. Health data relied on routinely vital statistics, hospital admission records, specific morbidity registers, and cancer and congenital abnormalities registries. our revision identified an overall lack of national surveillance programmes of ICSs, rather than gaps in individual dimensions of surveillance. The epidemiological approaches reviewed provided methods, some of which could be adopted for an EPHT in ICSs. However, a large proportion of examples suffers from poor exposure characterization, relying on a qualitative definition approach, which cannot account for the multiple pathways that take place in ICSs. Use of more individual data from health registries combined with improved environmental data collection and exposure assessment would improve future surveillance.

When is epidemiological research a helpful response to industrial contamination?

Epidemiologic research is intended to advance scientific understanding and is one of the possible actions in responding to an episode of industrial contamination. However, it is important to recognize that such studies are not a substitute for public health measures to identify the source of exposure, reduce or eliminate it, and take measures to prevent future events. The merits of initiating an epidemiological study that directly examines the relationship between exposure and disease in the affected population need to be carefully considered. There may be benefits in responding directly to the community's concerns, providing information to help generate resources to address the problem, and offering an opportunity to learn more about the pollutant health effects. However, there are also costs in the form of financial burdens of the research and prolonged period required to conduct studies, raising unrealistic expectations about what a study will provide, and not utilizing quantitative risk assessment as a more rapid and potentially more informative alternative to a new study. Where data systems are in place, risk assessment combined with health surveillance may often be the most efficient, informative response to the exposure event. New epidemiological studies are most likely to be valuable: - when there is little prior knowledge about the pollutant; - when exposure and health outcome can be accurately measured; - when there is not strong confounding; - when the size of the exposed population is adequate; - when the health consequences of the exposure are observable soon after the exposure occurs. The balance between costs and benefits of research may vary across settings, depending in part on the economic resources available to pursue new knowledge versus managing a threat to public health and in part on the nature of available environmental health surveillance data collection systems. Before initiating an epidemiological study, it is important to be certain that the goals are attainable for the research and that the research itself will support - rather than interfere with - pursuit of needed public health actions.

The rise of BioBlitz: Evaluating a popular event format for public engagement and wildlife recording in the United Kingdom

ABSTRACT“BioBlitz” events are popular local wildlife surveys often engaging public audiences in a race against time to find, identify, and record as many different species as possible in a given timeframe.This study provides baseline assessment of the value of BioBlitz as a tool for public engagement and collection of environmental data in the United Kingdom. We conclude that, collectively, BioBlitz events provide participants with an enjoyable learning experience, engage new audiences in biodiversity issues, and inspire positive action.Challenges of verification and consolidation of BioBlitz records make the value of these data to the wider environmental sector difficult to quantify.

Using data from schools to model variation in soil invertebrates across the UK: The importance of weather, climate, season and habitat

Soil invertebrates play important roles in nutrient cycling, the development of soil structure, food webs and even climate regulation. It is likely that climate change will have far-reaching impacts on soil invertebrates but a lack of information about how soil invertebrate populations vary with soil characteristics and climate make projections difficult. To address this gap, we present the results of a large-scale citizen science project that examined the abundance of soil macro-invertebrates across the UK.The abundance and biomass of twelve invertebrate groups were recorded by school children using standardised protocols on six occasions over two years. Using these data, we examined the relative impact of local habitat and soil characteristics, and weather and climate, upon these taxa.The abundance of many soil invertebrate groups varied with season and small-scale habitat factors. We found that the abundance and biomass of earthworms was strongly correlated with soil moisture. There was, however, little evidence that large-scale variation in soil invertebrate abundance could be explained by spatial variation in climate.Given the importance of earthworms for soil processes, periods of dry weather may reduce their ability to undertake nutrient cycling and the provision of other services such as food for invertivorous species. Future analyses of the impacts of climate change on soil invertebrates may usefully consider variables such as frequency of rain, rather than monthly or seasonal averages more widely used.Our results were generally in accord with patterns expected from previous literature, providing important quality assurance. This indicates that this could be an effective scheme for long-term monitoring of soil invertebrates and that it is possible to utilise educational establishments as a forum for large-scale environmental data collection. Not only can this deliver valuable environmental data, but also it can engage school children in the collection of scientifically valuable data.

Automated Image Analysis of Offshore Infrastructure Marine Biofouling

In the UK, some of the oldest oil and gas installations have been in the water for over 40 years and have considerable colonisation by marine organisms, which may lead to both industry challenges and/or potential biodiversity benefits (e.g., artificial reefs). The project objective was to test the use of an automated image analysis software (CoralNet) on images of marine biofouling from offshore platforms on the UK continental shelf, with the aim of (i) training the software to identify the main marine biofouling organisms on UK platforms; (ii) testing the software performance on 3 platforms under 3 different analysis criteria (methods A–C); (iii) calculating the percentage cover of marine biofouling organisms and (iv) providing recommendations to industry. Following software training with 857 images, and testing of three platforms, results showed that diversity of the three platforms ranged from low (in the central North Sea) to moderate (in the northern North Sea). The two central North Sea platforms were dominated by the plumose anemone Metridium dianthus; and the northern North Sea platform showed less obvious species domination. Three different analysis criteria were created, where the method of selection of points, number of points assessed and confidence level thresholds (CT) varied: (method A) random selection of 20 points with CT 80%, (method B) stratified random of 50 points with CT of 90% and (method C) a grid approach of 100 points with CT of 90%. Performed across the three platforms, the results showed that there were no significant differences across the majority of species and comparison pairs. No significant difference (across all species) was noted between confirmed annotations methods (A, B and C). It was considered that the software performed well for the classification of the main fouling species in the North Sea. Overall, the study showed that the use of automated image analysis software may enable a more efficient and consistent approach to marine biofouling analysis on offshore structures; enabling the collection of environmental data for decommissioning and other operational industries.

Effect of Environmental Thinking through Architectural Design Studio Education

Effect of Environmental Thinking through Architectural Design Studio Education Assoc. Prof. Shahira Sharaf Eldin, Ass. Prof. Mustafa Mohammed Elwan Abstract Complaints about the poor performance of architects and the declining quality of buildings have been widespread and were blamed not only on the architects but on what was thought to be the poor quality of architectural education. This paper explores the benefits of integrating comprehension of environmental studies in architecture pedagogy. This was accomplished through Environmental control core course offered for last year architecture level. A project was conducted with students in Architecture Department, Tanta University. A problematic of design entitled designing an environmental friendly restaurant in three different sites in Egypt, was given to students. First, students begin their project by site's environmental conditions data collection collected from the literature and from observations in studio practices. Then they begin their analysis using environmental software. At the second stage, students are expected to develop their designs through selecting environmental treatments in accordance with environmental comprehension and data for each site. In last stage, evaluation of environmental efficiency of suggested projects and their rational forms' development, which were the main targets of this study, were investigated. Best environmental treatment and energy saving were the main assessment aspects. Also, students compare forms created with their studied process. As a result of the following course, students were trained to thoroughly transform their architectural projects forms with respect to environmental conditions and energy saving. Finally the paper use these finding to assure the need of environmental control course as a powerful tool of learning in architecture education and comprehensive approach that illustrate the relation between design and environmental studies to enhance the performance of architects and the quality of building design . Full Text: PDF DOI: 10.15640/jea.v5n2a8

Energy-Efficient Data Collection Scheme for Environmental Quality Management in Buildings

How to efficiently collect sensory data for supporting energy-efficient operation of buildings has become a great challenge, especially for large-scale networks in buildings. In this paper, a spatio-temporal compression-based optimized clustering scheme is proposed for energy-efficient environmental data collection in buildings. In the scheme, first, according to the establishment of a cluster, an adaptive dynamic cluster head selection method for prolonging the lifetime of sensory nodes in buildings is developed. Meanwhile, to further reduce energy consumption, we construct the dynamic optimal quantity of the cluster heads solution method to achieve minimum energy consumption. Moreover, the spatio-temporal correlations of sensory data are explored in the data sampling and transmission processes, which can decrease the amount of data transmission and further extend the lifetime of the entire data collection network. The proposed scheme provides sensing data with high quality for environmental quality management in buildings and supports energy-efficient building operation. Finally, the simulation results show that the proposed scheme obtains obvious advantages in energy consumption compared with other related schemes, and the lifetime of the proposed scheme is also longer than others when it maintains high reconstruction precision.

Modeling and experimental evaluation of an improved amphibious robot with compact structure

Abstract This paper describes an improved three-dimensional (3D)-printed, low-cost, multi-functional, high-maneuverability, high-concealment, turtle-inspired mobile amphibious spherical robot for environmental monitoring and data collection. The major challenge in developing such a robot lies in its limited physical size and compact structure that allows for only one type of propulsion system to be used both on land and in water. This paper focuses on the optimization of the kinematic and hydrodynamic model of the amphibious spherical robot, so as to improve the control accuracy and stability of the robot. In order to optimize some kinematic and dynamic modeling parameters of the robot, such as the drag coefficient of robot, the angular velocity and swing angle of each joint, a solid model of the 3D-printed robot was built by SolidWorks. Our simulation results and theoretical calculations confirmed the validity of the virtual model and facilitated identification of key parameters in the design. The correctness of the modeling was demonstrated by the stability of consecutive crawling and underwater movements, providing a basis for driving and controlling methods for this amphibious robot, as well as guidance for the robot's gait trajectory. Combining the robot's crawling mechanism with related simulation results, an optimized prototype of the 3D-printed amphibious spherical robot was constructed. A series of crawling experiments on a common floor were performed with the improved robot prototype, which was also done using the previous robot. The results were evaluated by a novel optical positioning system, NDI Polaris. Moreover, several experiments were carried on land crawling and underwater swimming to verify the performance of the improved amphibious spherical robot. Comparison of experimental and simulation results demonstrated the improved robot had better amphibious motion performance, as well as more potentiality and applicability to the real structures.

Surface coal mine permit application for successful reclamation, semi-arid shortgrass prairie (Wyoming, USA)

Approximately 40% of USA coal originates in an ecologically sensitive area of semi-arid shortgrass prairie in Wyoming. Before a surface coal mine can begin operation in the USA, it must secure a mining permit and comply with regulations and performance standards under the USA Surface Mining Control and Reclamation Act (SMCRA), other federal environmental acts, and state programs. The Wyoming Department of Environmental Quality (WDEQ)/Land Quality Division (LQD) administers Wyoming’s coal regulatory program. The permit application and bonding process for the largest surface coal mine permit in the USA, North Antelope Rochelle Mine (NARM) located in short grassland prairie in the northeast Wyoming, is discussed. The permit application process begins with the collection of baseline environmental data that characterizes premining conditions of the permit area. The permit application includes adjudication information, baseline information, mine and operation plans, and reclamation plans. Fulfillment of permit commitments and requirements of rules and regulations are inspected monthly by the LQD’s representative in the field. Before a mine permit is issued, the mine operator must submit a reclamation bond to secure the performance of reclamation obligations that is later revised annually. In Wyoming, four reclamation bond release phases indicate the completion of various stages of the reclamatikon process. NARM’s specific bond release verification cirteria, performance standards, and field verificatoins of bond release phases are discussed. The Bond Release Geodatabase (a GIS/GPS approach) was developed for this mine to monitor progress in meeting criteria and performance standards for incremental bond release. The Bond Release Geodatabase significantly reduces the time needed to track bond release progress, reach agreement between operator and regulator, and improve the state inspector’s ability to assess reclamation adequacy and progress.

EVALUATING ENVIRONMENTAL CONSIDERATIONS WITH CHECKLIST AND DELPHI METHODS, CASE STUDY: SURAN CITY, IRAN

One of the major environmental concerns is to ensure that projects and projects are operational in accordance with the provisions and commitments contained in the report of the evaluation studies approved. In order to assess the extent to which environmental considerations are implemented, assessment reports are for reporting to supervisory organizations to ensure uniformity and procedural unity in their reporting process. The most practical methods are checklist. This study presents the evaluation process considerations environmental criteria, data collection and validation addressed and the plans and projects, including studies of environmental assessment includes the site of the elimination of waste, integrated cooking facilities, four stations, cement factory, the reservoir dam and the water pipeline transmission line by determining the scale and pollutant indicators separately for each case in the city of Suran in the south-east of Iran. Plans and projects that have actual effects on the environment of the studied area are weighted according to experts or Delphi. It can be concluded that according to the type of bricks and the type of fuel us ed by the factory (fuel oil), emissions such as emissions of fluorine from non-metallic minerals such as clay and compounds of nitrogen oxides and sulfur at the outlet of smoke the furnace has actual effects on the environment. Also, the slowing of the flow of water, coupled with low recharge, has increased the number of mineral particles and organic matter deposits. Finally, the status of the existing environmental monitoring program process in Iran has been studied and a new upgraded process is being proposed and proposed.

Lostrego: A distributed stream-based infrastructure for the real-time gathering and analysis of heterogeneous educational data

The quick technological evolution of the last decades has also reached learning environments, where the use of networked computing devices such as laptops, smartphones, tablets, IoT devices, servers, etc. is continuously growing. In particular, those computerized learning environments have the potential to track the activity of teachers and students in them, which enables the development of innovative applications that enrich the learning process by analyzing the collected data. The majority of related work in this field has been centered on batch gathering and analysis of the data. However, in order to integrate more reactive applications, there is a need for an infrastructure that enables the real-time collection and analysis of data in learning environments. Such an infrastructure should be scalable and flexible enough to cope with heterogeneous data coming from different types of learning settings. This paper presents Lostrego, a stream-based, modular, scalable and flexible distributed infrastructure that allows the gathering and analysis of educational data from heterogeneous data sources in a real-time fashion. Lostrego applications are composed by interconnected services that can be reused in different courses. The results of the evaluation of Lostrego in two editions of a computer programming course with 233 students and 384,702 gathered events are also reported.

An Anomalous Noise Events Detector for Dynamic Road Traffic Noise Mapping in Real-Life Urban and Suburban Environments.

One of the main aspects affecting the quality of life of people living in urban and suburban areas is their continued exposure to high Road Traffic Noise (RTN) levels. Until now, noise measurements in cities have been performed by professionals, recording data in certain locations to build a noise map afterwards. However, the deployment of Wireless Acoustic Sensor Networks (WASN) has enabled automatic noise mapping in smart cities. In order to obtain a reliable picture of the RTN levels affecting citizens, Anomalous Noise Events (ANE) unrelated to road traffic should be removed from the noise map computation. To this aim, this paper introduces an Anomalous Noise Event Detector (ANED) designed to differentiate between RTN and ANE in real time within a predefined interval running on the distributed low-cost acoustic sensors of a WASN. The proposed ANED follows a two-class audio event detection and classification approach, instead of multi-class or one-class classification schemes, taking advantage of the collection of representative acoustic data in real-life environments. The experiments conducted within the DYNAMAP project, implemented on ARM-based acoustic sensors, show the feasibility of the proposal both in terms of computational cost and classification performance using standard Mel cepstral coefficients and Gaussian Mixture Models (GMM). The two-class GMM core classifier relatively improves the baseline universal GMM one-class classifier F1 measure by 18.7% and 31.8% for suburban and urban environments, respectively, within the 1-s integration interval. Nevertheless, according to the results, the classification performance of the current ANED implementation still has room for improvement.