Studies in Indian Place Names (UGC Care Journal)
ISSN: 2394-3114
Vol-40-Issue-60-March -2020
P a g e | 2304 Copyright ⓒ 2020Authors
Landslide Monitoring Using Wireless Sensor Networks- A Case Study
Kanchan S Bhosale
Department of Electrical Engineering,
Smt. Indira Gandhi college of Engineering, NaviMumbai,Maharashtra
V. P. Patil
Department of Electronics andtelecommunication
Engineering,
Smt. Indira Gandhi college of Engineering,
Navi Mumbai, Maharashtra
Rajesh Kulkarni
Department of Computer Engineering,
Smt. Indira Gandhi college of Engineering,
NaviMumbai,Maharashtra
Shital Chawre
RMT Nagpur University,
Abstract—Monitoring of natural hazards is the need of the
hour. Monitoring helps us in detecting landslides, waterlogging at
railway tracks. This paper presents a warning system of weather
parameters, landslides using microcontroller NODEMCU 8266
on WIFI sensor networks, BH1750 ambient light sensor,Rain
drop sensor, Microwave radar sensor for motion detection, Node-
MCU ESP8266 are selected for landslide warning system. We
present the results on thinger.io cloud platform detected from the
sensors integrated to it. Real time data acquisition, transmission
and remote display on cloud is the feature of our proposal.
Thinger.io also has alarm switch to alert in case of values go
beyond threshold. The device in the results showed that the
system can transmit data via WIFI network automatically when there are changes from the threshold value.
Keywords— Landslides; Warning system;Sensor; Thinger.io;
NODEMCU8266
I. INTRODUCTION
As per [22]: ―Due to heavy rainfall from 10th to 17th July, 2019, two landslides occurred at Amiya Nagar, Chandmari and at NilachalpurBezbaruah Nagar, Guwahati, Assam. On 10th July 2019, a part of the road along with the retaining wall collapsed, along the approach road to the hills, near Holy Child School, Chandmari and on 16th July 2019 a boundary wall collapsed at Nilachalpur, Bezbaruah Nagar (N 26° 09' 29.0'' & E 91° 42' 45.3'') and damaged a house‖. This is one such incidence being referred among thousands of such incidents happening in India. As per [23]: “India is vulnerable, in varying degrees, to a large number of natural as well as man-made disasters. 58.6% of the landmass is prone to earthquakes of moderate to very high intensity; over 40 million hectares (12% of land) is prone to floods and river erosion; of the 7516 km long coastline, close to 5700 km is prone to cyclones and tsunamis; 68% of the cultivable area is vulnerable to drought and hilly areas are at risk from landslides and avalanches. Vulnerabilityto disasters/emergencies of Chemical, Biological, Radiological
and Nuclear (CBRN) origin also exists. Heightened vulnerabilities to disaster risks can be related to expanding population, urbanization and industrialization,development within high-risk zones, environmental degradation and climate change. It can also be related to increase in terrorism around the Globe” [23]. Wireless sensor networks are prevalent as low cost deployments for measuring and monitoring sites [1] for landslide hazards. The architecture in [1] consisted of motes deployed in urban forests for data collection and persistent storage, data collection done via 802.15.4,visualization, queries are facilitated through web service interfaces. Wireless sensor networks can be deployed for monitoring environmental disasters, sense the data and forward for analysis with minimum delay[2].
Landslides are movement of rock, earth resulting in casualties and economic losses. sensing data using spaceborne synthetic aperture radar (SAR) and optical remote sensing, airborne light detection and ranging (LiDAR), ground-based SAR and terrestrial LiDAR, incorporating in-situ surveying measurements and observations of environmental factors are mostly used to tackle landslides[4].
The paper is organized as followed: section I gives a brief perspective of landslides, their effect, monitoring mechanisms, Section II deals with review of take of various researchers works for landslide monitoring pertaining to generic and railway tracks, Section III deals with the case study conducted for monitoring and capturing landslide and other weather parameters data and last section concludes the case study.
II. LITERATURE REVIEW
In 2015, Razvan and Andreasanget al. [1] Insisted variations in soil texture and geometry depend on biological mechanisms and differences in the physical environment, because many soil insects and biotic animals are sensitive to abiotic factors such as soil moisture, temperature and light.
Studies in Indian Place Names (UGC Care Journal)
ISSN: 2394-3114
Vol-40-Issue-60-March -2020
P a g e | 2305 Copyright ⓒ 2020Authors
For this reason, any field study on soil biota requires soil temperature, soil moisture and other physical measurements.
In 2009, ManeeshaVyet al. [2]used the geophysical sensors viz; pore pressure transducers, soil moisturesensors, geophones, stain gauges and tiltmeters, based ontheir relevance in finding the causative geological factors forinducing landslides under heavy rainfall conditions.In their system they used heterogeneous network composed of wireless sensor nodes,Wi-Fi, and satellite terminals for efficient delivery of realtime data to the data management center, to enablesophisticated analysis of the data and to provide landslidewarnings and risk assessments to the inhabitants.
As per 2010 Yin zihonget al.[3]:―Collapses and slides caused by the earthquakes in China mainly take place in the frequently-earthquake-hit western region, i.e. Shanxi province.Proposed QUAKE/Wmodel is intended as the first step in a dynamicearthquake analysis.Once the QUAKE/W analysis iscomplete, the resulting stresses and pore-water pressures canthen be used in SLOPEIW (another software product inGEO-SLOPE Office) to analyze the stability aspects of theproblem.‖.
In 2018 Zhao et al.[4] discussed multipleremote sensing techniques such as SAR, optical, LiDAR, ortho-photo, and DEM obtained fromspaceborne, airborne, and ground-based platforms to monitor landslide processes.
In 2014 R. Tejaet al.[5] proposed idea of land-slide detection and monitoring systemwith various geo-physical sensors forming a heterogeneousnetwork (MOTE) and transmitting the data to a ground station.The Data Acquisition System at the control station isequipped with all the necessary protection equipmentfor the officials to takenecessary steps for disaster protection.
In 2018, Bo Gan.et al. [9] combinedData acquisition with GPRS network, to realizeremote transmission of monitoring area data. In their test bed the sensor nodes in the monitoring area had a large numberof nodes and the collected environment information was complicated. The monitoring of the landslide area was effective. They focused on node wirelesscommunication and networking test, sensor data acquisition and transmission test,node communication distance and power consumption test.
In 2003 Wang.et al [12] conclude that grain size of sand plays an important role in movement of a landslide mass and pore-pressure build-up after failure. The optimal density index, atwhich thepore-water pressure build-up after failure reachesits maximum, is different for samples with differentgrain sizes.
In 2007 Arnhardt.et al[13] proposed work provides a substantial contribution to the development of methods and technologies for earlywarnings with regard to mass movement events.
In 2012 Emanuele. et al[14] implemented early warning system(EWS).EWS is not just a cluster ofmonitoring systems
or the forecast of failure, but it also involvesother aspects such as the identification of risk scenarios, emergency plans, societal considerations, and public awareness.EWS include data acquisition, transmission and maintenance of measuring instruments.
In 2012 Lagomarsinoet al[15] proposed warning system is named Sistema IntegratoGestioneMonitoraggioAllerta, and it is based on a set of spatiallyvariable statistical rainfall thresholds
In 2017, Mustafa RidhaMezaalet al.[19] used high-resolution airborne light detection and ranging (LiDAR) toapproachAs employed to optimize the parameters (i.e., scale, shape, andcompactness) of the multiresolution segmentation algorithm for landslide identification and fordifferentiation from non-landslides.
In 2019, F. B. Setiawanet al. [21] method is to shoot a laser beam at thetarget plate. The target plate is in an area that is prone tomovement, while the laser shooter is placed in a relativelystable place. The position of the point shot by the laser beamis monitored using a camera. Then the signal from thecamera is connected via the internet network to the datacenter. The server-centered process is done to minimize and simplify the process of the microcontroller, from storagecommunication networks TCP / IP wireless, UTP cable, or communication through a GSM modem. Workflow scheduling in the cloud sectorgenerate accurate landslide maps. Their study proposes the use of recurrent neural networks (RNN).The supervised,processing, to displaying data. Information displayed througha web interface can be accessed by the user
III. PROPOSED WORK
In India, there is no such immediate communication systemthat addresses the common people about the landslide on railway immediately. In metro cities every day most of people travel in train for job purpose, for some other reason every day in every season. During the rainy season most of landslides and water logging happened on track in that case, the major problem is thatof the delay occurring in sending alerts to the concerneddepartments and common people residing in remote areasabout the landslide alert. So, there is a needformaking an automatic alert system which will immediately monitor andsimultaneously sends the alert message to everyoneconcerned without any man power required and send alert signal to people concern. To meet this requirementthis automatic landslide alert system is designed and developed. The main aim of the proposed systemis to develop a Real-time detection of landslides on railway track and also todevelop an online forum so that the people can communicatewith the concerned authorities.
The case study involved the following: students of final year Instrumentation Engineering of Smt. Indira Gandhi College of Engineering, Ghansoli, Navi Mumbai and their mentors designed a board comprising of BH1750 ambient light sensor, Rain drop sensor, Microwave radar sensor for motion detection, Node-MCU ESP8266 for measurement and
Studies in Indian Place Names (UGC Care Journal)
ISSN: 2394-3114
Vol-40-Issue-60-March -2020
P a g e | 2306 Copyright ⓒ 2020Authors
calibrations. Light sensor BH1750 has I2C interface. It can detect at wide range and high resolution. With BH1750 light sensor intensity can be directly measured by luxmeter without calculations. RCW radar sensor module is human body induction switch module intelligent sensor. It uses Doppler radar to sense the presence of intruder.DH11 is low cost digital sensor for sensing temperature and humidity measures the surrounding air. This sensor uses thermistor and capacitative humidity sensor. Rain drop sensor is used for measuring rainfall intensity. The module includes rainboard and control board upon sensing create the path of circuit resistance that are measured via OP-AMP. The readings were collected from Ghansoli railway track, a small suburb in navi Mumbai. Fig.1 depicts the proposed architecture of the system. All sensors are interfaced with Node MCU wifi module. Calibration data are captured by thinger.io open source platform. Fig.2 shows live installation of board and readings collections. Fig.3 depicts weather parameters such as temperature, motion, rain, light intensity and geolocation of the device on Thinger.io dashboard.Thinger.io is a open source cloud IoT Platform. Any kind of device can be integrated to Thinger.io allowing bidirectional communications with all of the devices. A Data Bucket stores IoT data interfaced to it in an scalable, efficient and affordable way, that also allows real-time data aggregation. A switch is facilitated on the dashboard for alerts.
Fig. 1. Proposed Architecture
Fig. 2. Setup Installation near railway track
Fig. 3. Dash Board representation on Thinger.io
Fig. 4. Real Time Export from Thinger.io Bucket
Studies in Indian Place Names (UGC Care Journal)
ISSN: 2394-3114
Vol-40-Issue-60-March -2020
P a g e | 2307 Copyright ⓒ 2020Authors
IV. CONCLUSION
This paper has presented a wireless sensor based landslide monitoring system. The case study involved calibrations reading using WSN based board having sensors (BH1750 ambient light sensor, Rain drop sensor, Microwave radar sensor for motion detection, Node-MCU ESP8266). The future work involves designing algorithm for efficient landslide monitoring system.
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