A Smart Way To Monitor Environmental Threats In Urban Areas Through State-Of-The-Art Sensing Technologies

July 16, 2018 i-Neighbour Smart Community 0 Comments



As the world is moving forward and becoming more advanced in lifestyle and technology, the Earth continues to deteriorate due to various factors that are causing threats to the overall environment and impacting on human lives in general. Earth Day 2018 highlighted the most pressing environmental concerns such as Ocean and Plastics, Rising Seas, Extreme Weather, Famine, Water Supply and many more. Out of the numerous environmental issues, there are four which have a direct impact on our residential environment, namely Climate Change, Air /Water Pollution, Floods and Landslides.

Today, more than half of the world’s population lives in urban areas due to jobs availability and wealth, and it is projected that urban population will increase to 70% by 2050. Influx of population into the urban area exacerbates the availability and quality of air and water, creates waste-disposal problems, and causes high energy consumption.

The environment is another important factor in determining the quality of life and health of urban dwellers. A good quality urban environment will surely make it more attractive and healthier for people to live, work and prosper. On the other hand, the degradation of the environment through air pollution, poor road traffic, floods and climate change, may have negative impacts on the human health and their well being.

This article will go into detail on each of the four environmental threats for better understanding and suggest a way on how smart technology can be utilized to better monitor these threats for the benefit of the larger community.


Climate Change Is On The Upward Trend


Based on the report “Global Risks 2018: Fractures, Fears and Failures” by the World Economic Forum, emissions of carbon dioxide (CO2) had risen for the first time in four years, bringing atmospheric concentrations of CO2 to 403 parts per million, compared with a pre-industrial baseline of 280 parts per million. The increase in the world’s CO2 concentrations in the future is almost certain, thus this issue has been gaining attention as one of the major environmental threats. Having absorbed 93% of the increase in global temperatures between 1971 and 2010, the world’s oceans continue to get warmer and studies suggest that their capacity to absorb CO2 may be declining. Research also suggests that tropical forests are now releasing rather than absorbing the carbon dioxide.

This claim is backed up by NASA, which has also confirmed that the amount of carbon dioxide levels in the atmosphere have increased "from 280 parts per million to 400 parts per million in the last 150 years", due to burning fossil fuels, intensive agriculture, and other human activities. This has resulted in an increase of global temperatures by one degree Celsius over pre-industrial levels. Besides the increased in extreme weathers, according to NASA, this rise in temperature also has raised the sea levels by 1-4 feet since 2010 thus causing Arctic ice caps to shrink, and increased growing season.

Global warming is the increase of Earth’s average surface temperature due to the emission of greenhouse gases such as carbon dioxide from burning fossil fuels or from deforestation, which subsequently trap heat that would otherwise escape from the Earth. The following graph illustrates the change in global surface temperature relative to 1951-1980 average temperatures. The year 2016 marks as the warmest on record and the year 2017 is ranked as the second warmest since 1880, according to an analysis by NASA (NOAA Global Climate Report, 2018).

Global average surface temperature data from the NASA Goddard Institute for Space Studies (2017)


Heat waves and warming temperatures pose a serious threat for human settlements worldwide, especially in urban environments.

This is because modern cities are densely packed with buildings, and they lack green space and vegetation, which in turn limits shading and evapotranspiration. Research shows that the increase in temperature or heat burden may cause heat-related illness such as heat stroke, heat syncope, heat exhaustion, and heat cramps. For every 1 °F (0.6 °C) increase in heat wave intensity, there is a 2.49% increase in the risk of death. Furthermore, every one-day increase in heat wave duration results in a 0.38% increase in mortality risk (Anderson & Bell, 2011).


Air And Water Pollution Threat Is Worse In Urban Areas


Both short and long-term exposure to ambient air pollution can lead to reduced lung functions, respiratory infections and aggravated asthma. According to reports from the World Health Organization (WHO), air pollution is the cause of over 34% of deaths from stroke, lung cancer, and chronic respiratory disease, and 27% of deaths from ischaemic heart disease. The combined effects of ambient (outdoor) and household air pollution cause about 6.5 million premature deaths every year.  Air quality is particularly bad in cities, and this situation is going to get worse as more people move into cities.

Today, an estimated 92% of the world’s population lives in areas where air pollution exceeds WHO safety limits.

Pollutants with the strongest evidence for public health concerns are particulate matter (PM), ozone (O3), and nitrogen dioxide (NO2). The health risks associated with particulate matter of less than 10 and 2.5 microns in diameter (PM10 and PM2.5) is especially well documented. PM is capable of penetrating deep into lung passageways and entering the bloodstream causing cardiovascular, cerebrovascular and respiratory impacts. In 2013, PM was classified as a cause of lung cancer by WHO’s International Agency for Research on Cancer (IARC). It is also the most widely used indicator to assess the health effects from exposure to ambient air pollution (WHO, 2016).


World Air Pollution Map by WHO (2016)


Urban populations are also exposed to water quality problems. The non-point source pollution picks up pollutants such as excess nutrients from fertilized lawns, heavy metals and petroleum hydrocarbons from our cars, and fecal coliform bacteria from our pets and septic systems which can cause serious health risks.  The immediate concerns center on bacterias and viruses which can affect health level resulting in diarrhea, fever, severe cramping and vomiting. Long-term effects of polluted water result in an overall decline in ecosystem function, which results in the continued decline in terms of water quality, aquatic habitat as well as increased health risks. 


Floods Risk Is Real For Urbanites


As this article is being written, Western Japan is being hit by 3 times its normal annual torrential rainfall. The floods have caused more than 100 dead and 58 missing in Okayama Japan. Floods are indeed one of the greatest environmental threats that can affect millions of people, around the world. A flash flood, which can develop in less than a few hours, is primarily caused by heavy rainfall and thunderstorms. Extensive rainfall over a long period of time will also lead to flooding of geomorphic low-lying areas.

Floods often cause damage to homes and properties, potential loss of lives, and deterioration of health conditions owing to waterborne diseases.

Today, weather forecast mostly relies on weather satellites that collect observations globally. While weather forecasts are getting better with more advanced prediction algorithms, we need higher spatial resolution rainfall data in order to measure exactly the amount of precipitation in a specific area. This is because the rainfall and soil characteristics could be very different from place to place. By observing a long-term temporal dataset, it is possible to develop a nationwide framework for flood forecasting (Chang, et. al., 2014; Selvanathan et. al., 2018).


Flooded Residential Areas near Lake Houston following Hurricane Harvey (2017) 
[Photo by Win McNamee/Getty Images]


For urban dwellers, the risk of having Pluvial (Surface Water) Flooding where flooding occurs when an extremely heavy downpour of rain saturates drainage systems and the excess water cannot be absorbed, is high. Based on “Pluvial (rain-related) Flooding in Urban Areas: the Invisible Hazard”, pluvial floods have recently been identified as the type most likely to increase in severity as a result of climate change. They are also the most difficult to manage because they are difficult to predict and it is challenging to provide adequate warning times to the affected population.

As Urban Development Continues, The Risk Of Landslides Increase

Every year, over one million people are exposed to landslide hazards around the world.

Due to the recent climate change, it is likely that the decrease of permafrost areas; changes in precipitation patterns and increase of extreme weather events will influence the weather-related mass movement activities. Moreover, the spread of urban settlements and transportation networks into landslide prone hilly areas is increasing the potential occurrence of landslides, land subsidence and slope failures.


Landslide hits the residential areas in Nova Friburgo, 130 km north of Rio de Janeiro, Brazil (2011)


In order to develop an effective early warning system for landslides, it is important
to perform a comprehensive assessment about the mechanisms of the landslide, including continuous monitoring of the slope stability, surface runoff, intra ground movement, underground water, and rainfall. The monitoring system may consist of a variety of sensors such as in-place inclinometer, multiple strain gauge, piezometer, tiltmeter, rain gauge, infrared camera, Global Navigation Satellite System (GNSS), LIDAR system and Ground Based Synthetic Aperture Radar (GBSAR) (Koo et. al., 2015, Zhao et. al., 2018).


Tapping On Smart Technology In Mitigating Environmental Threats In Residential Areas.

For residential communities, it is important to understand the quality of our residential environment in order to protect our families, assets and our entire community. The responsibility shouldn’t be placed on the shoulders of the authorities; as a member of a community, we have a part to play in monitoring the environment that we are living in to enable us to mitigate the risks as they come.

Having sufficient knowledge about our environment gives the community the power it needs to forward any issues to the authorities for remedial actions.

On 11st December 1993, Block One of the Highland Towers in the state of Selangor Malaysia collapsed, killing the life of 48 individuals and causing two other residential blocks to be evacuated for safety reasons. The cause of the catastrophe was a major landslide in Taman Hillview, Ulu Klang Selangor. Nobody expected the tragedy to happen, as everybody was minding their own business as usual on that day, even though the area had been receiving heavy rainfall for 10 continuous days.

That fated condominium was just erected for almost 2 years when the accident happened. Bukit Antarabangsa Development Project commenced the construction of the Highland Towers in 1991, and the construction had exposed the area’s soil to land erosion, the leading factor of the landslides. The water flow had not been managed properly and it had caused pipes burst at several locations on the hill, leading the surrounding soil to absorb the excessive water, and turning the soil into mud. By the end of November 1993, the hill slope had been saturated with water, and the water was even seen flowing down the hill slopes as well as the constructed retaining walls. Highland Tower tragedy was not the first case of landslides that have caused deaths and endangered human lives in residential areas, and it certainly would not be the last if the community who lives near hill slopes do not do anything about it, or leave the matter in the hands of the authority entirely.

From 1993-2011, around 28 major landslides were reported in Malaysia with a total loss of more than 100 lives. Moreover, from 1973-2007, the total economic loss due to landslides in Malaysia was estimated about US $1 billion.



The Block One of the Highland Towers Collapsed due to Massive Landslides


Apart from landslides, floods is another environmental threat that could endanger the lives and properties of residential communities. Floods tie to climate change as  the warmer the Earth gets, the more water it absorbs, which could result in heavier rains. For example, in Bandar Baru Ayer Itam, Pulau Pinang, Malaysia, an area consisting of 10,000 housing units, has been the scene of floods for the last two to three years. The failure of the retention ponds in two areas had led to the floods in these residential areas. Floods in Pulau Pinang also had caused a deadly landslide in  Tanjung Bungah that claimed the lives of 11 workers. Therefore, residential areas particularly at the hilltop or hillside need to find a way to monitor these threats in order to stay safe.

The first step for the community to do is to know the area that needs to be monitored through a set of environmental indicators.

Environmental indicators are simple measures in the form of numerical values that track the state of the environment over a period of time. Environmental indicators can be measured and reported at different scales. For example, a city may track the air quality along with the water quality and count the number of rare species of birds to estimate the health of the environment within their area. In another scenario, people living in hilly residential areas may track the variations in rainfall patterns and its impact on the slope stability and soil erosion.

A community can kickstart the monitoring of an environment with a set of environmental sensors installed at the appropriate site location for continuous data collection.

Environmental Services which a community can consider include:

1.   Air Quality Monitoring
2.   Scanning of Environment Service
3.   Environmental Risk Assessment Service


Overview of Intelligent Environmental Sensing Solution


For Air Quality Monitoring, the environmental data which can be collected include air quality indicators (PM10, PM2.5, O3 and NO2) and weather-related indicators (ambient temperature, humidity, and rainfall). The spatial and temporal environmental data collected at the cloud server will then be fused and processed by an AI-based (artificial intelligent) data analytics engine. For example, in the case of air quality assessment, the air quality indicators (PM10, PM2.5, O3 and NO2) are treated as a spatiotemporal process and a deep learning algorithm is used to construct a space-time prediction framework. Traditional linear-model methods such as autoregressive moving average (ARMA) method is not suitable for air quality prediction, because the air quality process is inherently nonlinear and its temporal trends and spatial distributions are greatly affected by various factors, such as air pollutant emissions and deposition, weather conditions and traffic flow. As compared to the traditional methods, the deep learning-based method uses multiple-layer architecture to extract nonlinear spatiotemporal air quality features, thus it has superior performance for air quality prediction.

Air Quality Prediction based on Deep Learning


These days, this kind of  data can be acquired on an hourly basis and sent to a cloud server in real-time for accurate monitoring. A community can install a weather station that consists of a few sensors enclosed by an industrial-grade chassis for outdoor operation. Sensors available in a Weather Station include Rain Gauge, Temperature & Humidity Sensor, Particle Sensor, and Ozone & Nitrogen Dioxide Sensor, which could produce traces of gases in the environment such as Hydrogen Sulfide, Chlorine, n-Heptane and etc. This Weather Station is not only affordable but the deployment has also been made easy for a community to initiate.

A Sample of Weather Monitoring Station



Air Quality Station


On top of monitoring the air quality, the community or developer can also engage with a service to scan the topography of the surrounding area to produce high-resolution geological map of their neighbourhood for better understanding of the surrounding area.  These collection data could be updated from time to time, or on a demand basis during/after an emergency incidence and it could also be uploaded to the cloud server for further processing.

Multiple photos of the ground can be taken as the drone flies along a flight path. These photos will then be processed to generate point clouds, digital elevation models (DEMs) and 3D terrain models. Detection and classification of the risk of the slope or structural instability is accomplished by using a machine-learning algorithm based on a deep auto-encoder network with multiple hidden layers. The results are integrated with measurements from rain gauges to produce a landslide susceptibility map. Since the majority of landslides are induced by heavy rainfall, it is thus crucial to continuously monitor rainfall and measure how landscape evolves over time, facilitating both civil protection operations and countermeasures.

This is a state-of-the-art solution that can enhance the quality of life for residential communities. Deployment of cameras, radars and drones to conduct surveillance in the most challenging environment provides the market with a simpler, faster and safer choice and presents data processing capabilities that are fast and efficient, using state-of-the-art cloud computing, cutting-edge software, and proprietary algorithms.

Drone also can be launched to perform aerial photogrammetry surveys for land subsidence and landslide detection.

Example of Geological Section showing Landslide


The monitoring system for landslide may consist of multiple sensors such as in-place inclinometer, multiple strain gauge, piezometer, tiltmeter, infrared camera, Global Navigation Satellite System (GNSS), and rain gauge. Modern technique such as Ground Based Synthetic Aperture Radar (GBSAR) can be used as it has proved it effectiveness. And upon collection of data from various sensors described in previous sections, comprehensive analysis can thus be performed. The outcome of this stage can lead to the establishment of a set of criteria for Early Warning (EW) System that consists of hardware and software as well as the criterias that relate the measured data to the risk levels of landslide. The hardware refers to the sensors, transmission system, storage system and others support units that perform the data collection of the slope whereas the software refers to the control and processing of the data, evaluation of the risk level, and sending the required information to the designated administrators to assist in making the decision of action. The working principle of the EW system is illustrated in the figure below.


Working principle of EW


The scanning service can also be obtained by developers who want to minimize risk while maximizing the return of investment on their development projects. The scanning service usually creates a flight plan and launches a drone to perform aerial surveys with a wider view and at different perspective for land developers and the data collected by the drone will then be processed into the desired deliverables with accurate measurements. By engaging with this service, developers will be able to  provide accurate 3D terrain models of the development areas, environmental analysis, accurate contour maps, surface assessment for drainage modeling, earthwork volume calculations, high altitude views of tall buildings, elevation mapping as well as panoramic images for marketing purposes.  All the information gathered from the service will provide developers with valuable insight for the project and is likewise a useful arsenal for marketing.


3D Terrain Model Generated by Photogrammetry Technique


By continuously monitoring these environmental indicators and observing their spatiotemporal changes, a set of criteria is determined for evaluating the risk level. The risk levels are defined not only by the extent and imminence of the potential hazards but also based on the actions to be taken in accordance with the risk levels.



Example of the risk levels and their corresponding actions are depicted in the following figure. The recommended actions are based on the inputs from the experts and the local authorities, and in accordance to standard practices outlined by international bodies such as World Health Organization (WHO), World Meteorological Organization (WMO), and International Consortium on Landslides (ICL).


Cost Effective is the Question?


But, the services sound expensive for a community to take on, doesn’t it? Definitely not! The advancement in technology and the widespread use of cloud server make smart sensing technology affordable to communities and developers these days.

An example of the price for a Topography Survey which could provide the community with accurate and geo-tagged topographic drawings of your premises and surroundings with features represented by contours, texts and symbols, plus Land Subsidence Detection as well as Exterior Building and Structure Inspection is estimated around USD 4500 for less than 250 residential units.

The market price for Air and Weather monitoring including the hardware is estimated to be  around USD 4,000 for a community of less than 250 units, whereas an Environmental Risk Assessment, which consists of preliminary slope assessment, an initial site investigation and topographic survey of the slope, borehole logging and soil samples collection for slope stability analysis, slope monitoring and early warning real-time monitoring of slope stability and ground movement and early warning system setup and risk assessment reporting for every 6 months is offered by the market starting at around USD 12,500 up to USD 125,000 depending on the amount of equipments setup as well as depending on the slope conditions.

Hence, these services are rather affordable, taking into consideration the greater benefits it provides to the entire community. Hence, it is essential for a community to be in the know about the living environment in order to be able to take appropriate measures with that information in ensuring the safety of the community.   


CONCLUSION


In this article, four major environmental threats concerning urban dwellers have been reviewed, namely global warming, air/water pollution, floods and landslide hazards. Understanding the potential threats of our residential environment is of great importance to ensure that our families are well protected. This can be achieved by continuously monitoring the quality of our residential environment through a set of environmental indicators. An intelligent environmental sensing and analytics solution could be deployed in residential areas to collect timely environmental indicators, and analyze their impacts through an AI-based data analytics engine. Scanning of  Environment is another service which could provide a community with a clear environmental overview of a surrounding area and its risks, and Environmental Risk Assessment Service can then be used to assess slopes and the potential of  landslides in an area.  State-of-the-art Smart Sensing technology is capable in assessing the most up-to-date environmental indicators and their associated risk levels. It is imperative for a community to detect trends in the environment and instantly communicate the results to interested parties for decision making and prompt actions that could guarantee the safety and well being of a community.



References:
[1]  World Economic Forum 2018?, Global Risks 2018: Fractures, Fears and Failures, viewed 10 July 2018, <http://reports.weforum.org/global-risks-2018/global-risks-2018-fractures-fears-and-failures/>.

[2] NOAA National Centers for Environmental Information 2018, State of the Climate:
Global Climate Report for January 2018, viewed February 25, 2018, <https://www.ncdc.noaa.gov/sotc/global/201801>.

[3] Anderson GB, Bell ML 2011.Heat Waves in the United States: Mortality Risk during
Heat Waves and Effect Modification by Heat Wave Characteristics in 43
U.S. Communities,” Environmental Health Perspectives, 119(2), pp. 210-218, doi:10.1289/ehp.1002313.

[4] Ambient Air Pollution: A Global Assessment of Exposure and Burden of Disease,
World Health Organization (WHO), 2016, ISBN: 9789241511353.

[5] Chang, Li-Chiu; Shen, Hung-Yu; Chang, Fi-John, 2014 “Regional Flood Inundation
Nowcast using Hybrid SOM and Dynamic Neural Networks,” Journal of Hydrology,
519 (Part A), pp. 476-489, doi:10.1016/j.jhydrol.2014.07.036.

[6] Selvanathan, Sivasankkar, Mathini Sreetharan, Seth Lawler, Krista Rand,
Janghwoan Choi, and Mathew Mampara 2018,A Framework to Develop Nationwide
Flooding Extents Using Climate Models and Assess Forecast Potential
for Flood Resilience,” Journal of the American Water Resources Association
(JAWRA), 54(1), pp. 90-103, doi.org/10.1111/1752-1688.12613.

[7] Koo V.C., Lim C.S., William Hii H.H., et. al, 2015, “Ku-band Ground-based SAR Experiments for Surface Deformation Monitoring,” IEEE 5th Asia Pacific Conference on Synthetic Aperture Radar, doi: 10.1109/APSAR.2015.7306288.

[8] Chaoying Zhao, Zhong Lu 2018. “Remote Sensing of Landslides – A Review,” Remote
Sens, 10(2), pp. 279, doi:10.3390/rs10020279.

[9] Donald Houston, Alan Werritty, David Bassett, Alistair Geddes, Andrew Hoolachan and Marion McMillan 2011, Pluvial (rain-related) Flooding in Urban Areas: the Invisible Hazard, Joseph Rowntree Foundation, viewed 25 March 2018, <http://eprints.gla.ac.uk/162145/7/162145.pdf>.

[10]  Stacy Hutchinson 2016, Urban water expert comments on water pollution in cities, Rio de Janiero, Kansas State University, viewed 9 July 2018, <https://www.k-state.edu/media/newsreleases/jul15/pollution73115.html>.

[11] Rahman 2017, Landslides Disaster in Malaysia: an Overview, Research Gate, viewed 11 July 2018, <https://www.researchgate.net/publication/321096764_Landslides_Disaster_in_Malaysia_an_Overview>.

[12] A Practical Landslide Monitoring Framework – How It Works
A White Paper by Yee-Kit CHAN

[13] Monitoring Air Quality Using A Deep Learning Model
A White Paper by Dr. Shing Chiang TAN and Dr. Voon-Chet KOO


Authors:

Voon-Chet KOO is currently a full Professor of Multimedia University. His research interest includes remote sensing technologies, signal processing, and embedded system design. Prof Koo has been a principal consultant for various government agencies and engineering firms since 2000. He has published more than 100 papers in refereed journals, international conferences, 2 books, and 9 patents. He is also the recipient of the inaugural Young Engineer Award by the Institution of Engineers, Malaysia in 2004. 

Prof. Koo has more than 20 years of experience in remote sensing and related technologies, particularly on high-resolution imaging system for environmental monitoring and earth resource management. He is a regular invited speaker in international conferences and has delivered guest lectures and technical workshops to various universities, government agencies and private sectors, including Malaysia, Indonesia, Singapore, Vietnam, Taiwan, Hong Kong, Japan, and the United States. 

Prof. Koo is presently the Director of Digital Lifestyle Research Institute, MMU, Past Chair of the Centre for Remote Sensing and Surveillance Technologies, MMU, Past Chair of the IEEE Geoscience and Remote Sensing Society Chapter, Malaysia Section, a registered Professional Engineer with Practicing Certificate, a Fellow of the ASEAN Academy of Engineering and Technology (AAET), and a senior member of IEEE. Prof. Koo is also the founder and the current CEO of a spin-off company of the university research centre. The company, iRadar, was incorporated in 2011 with primary focus to provide smart sensing solutions for environmental and vegetation growth monitoring. 




Norana Johar has a Bachelor of Science (Psychology) from Indiana University of Bloomington, USA and began her career in the sales & marketing department at FingerTec in 2000 to market biometrics solutions for time attendance and door access worldwide. Throughout her service, she has helped to develop and deliver technology-driven business services and solutions, provide excellent client service, and drive profitable revenue growth throughout her leadership and experience. She is now assuming the role of Group Chief Operating Officer at TimeTec Computing Sdn. Bhd., whereby she has vast experience in handling the business's global network. of resellers operations.

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