International Journal of Civil Engineering and Technology (IJCIET) Volume 9, Issue 6, June 2018, pp. 54–66, Article ID: IJCIET_09_06_007 Available online at http://iaeme.com/Home/issue/IJCIET?Volume=9&Issue=6 ISSN Print: 0976-6308 and ISSN Online: 0976-6316

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GIS AND SENSOR BASED RAIN WATER HARVESTING WITH ARTIFICIAL INTELLIGENCE SYSTEM FOR FREE LANDSLIDING

S. RinaMaiti Research Scholar, Department of Geography, Sri SatyaSai University of Technology & Medical Sciences, Sehore, Bhopal, Madhya Pradesh,

Dr. L. Mishra Professor, Department of Geography, Sri SatyaSai University of Technology & Medical Sciences, Sehore, Bhopal, Madhya Pradesh, India

ABSTRACT This article projects a combined idea to avoid and stop a landslide issue in built on GIS and sensor system applications method. This method is made out of three vital components, landslide susceptibility mapping utilizing remote- detecting procedures for susceptible determination of landslide spots downsized landslide simulation tests for approval of sensor network for landslide monitoring and in situ sensor network deployment for strengthened landslide observing. The investigation catchment site is the landslide situated in Darjeeling. Landslides have dependably been a standout among the most catastrophic natural phenomena. Nonstop observing and cautioning as early as possible about the beginning of such fiasco may lead to ignore loss of human lives. With this point we have built up an observing framework organized as WSN furnished with extremely sensitive sensors equipped for estimating real time direction and magnitude of the landslide relocation. The sensors are put in request to quantify the accurate value about the parameter of the landslide. Here GPS is utilized as a part of request to decide the area of the landslide event. The activities are watched and the gathered informational collections are consequently transmitted to an associated framework and the FLUX SENSOR which is utilized as a part of this study gives an ongoing data about the present condition of the observed slope. All the more such sensors are mounted on a specific region more ahead of time for a landslide prone and associated in a network ready to remotely convey and transmit online information to an observing focus.

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Key words: Darjeeling, Landslide, Prediction, Sensor, Soil Erosion, GIS. Cite this Article: S. RinaMaiti and Dr. L. Mishra, GIS and Sensor Based Rain Water Harvesting with Artificial Intelligence System for Free Landsliding, International Journal of Civil Engineering and Technology, 9(6), 2018, pp. 54–66. http://iaeme.com/Home/issue/IJCIET?Volume=9&Issue=6

1. INTRODUCTION Landslides are the noteworthy type of cataclysmic event that causes the loss of properties and lives, particularly in the precipitous zones. The sloping landscapes are described by high vitality with precariousness and inconstancy of the majority. Landslide contrasts from alternate mass development procedures and it is the development of the mass happens essentially along a discrete disappointment surface (Sumantra SB and Raghunath P, 2016). The inside unreformed plane slips the materials and deteriorates the mass and further development incorporates the stream component. In India, the majority of the sloping areas are portrayed with the landslide catastrophe. The Darjeeling Himalaya is a piece of Lesser Himalaya. The height of the district ranges from 500 m to 2500 m above MSL. Because of shifted geomorphology and neo-structural exercises, the locale is one of the exceedingly seismic tremor inclined territories. The primary shake sorts of the Darjeeling Himalayas are Pre-Cambrian high-review gneiss and quartzite, high-review schist phyletic and calc-silicate and quartzite. The real soils of this locale are described by high grouping of iron oxide with the absence of mineral and natural supplements. The sedimentary shake of youthful collapsed mountain advances the dynamic disintegration in Darjeeling Himalaya. This area is exceedingly powerless against landslides and the beginning of storm in the north India as a rule comes full circle into huge high precipitation over the Himalayan lower region belt (Pal R, 2016).

2. OBJECTIVE  Soil stabilization and free land sliding of rain water harvesting system. GIS and sensor based rain water harvesting with Artificial intelligence system.  WH techniques that store water as soil moisture work by preventing (or significantly reducing) water runoff from an area using structures to hold water and thus encourage infiltration, thus increases the proportion of rainfall entering soil storage, where it can later be used directly by plants.  To locate the feeble soil adjustment territory by utilizing GIS and taking preventive activities and to discover the likelihood of land sliding zone in well ahead of time by utilizing Sensor observing framework to avoid life misfortune.

3. NEED OF THE STUDY Continuous observing of ecological calamity are one of the prime need of the world. WSN is one of the real innovation that can be utilized for real time monitoring. WSN has the capacity of vast scale deployment, low cost, versatility, flexibility for various situations. WSN has its own particular restriction, for example, low memory, power, data transmission and bandwidth. The deployment and information recovery or gathering from geophysical sensors, the plan, development and deployment of WSN, the improvement of information accumulation and information collection calculations required for the system, and the system necessities of the deployed landslide detection system, information investigation.

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4. STUFY OF DARJILING HIMALAYAS Darjiling Himalayas Available records demonstrate a lamentable landslip happened on the 24th September, 1899, in and around Darjiling town because of extraordinary precipitation of 1065.50mm, executing 72 people and making tremendous misfortune land and property (Griesbach 1899-1900). The vast majority of these fifteen slides were bound to the dirt material overlying the gneissic rocks. The insecurity of the slopes steadily expanded because of dynamic retention of moisture from over the top rainfall and the cutting of slope inclines both for common and manufactured needs together with imperfect seepage. The second significant occasion of landslips in , Darjiling, Kalimpong and towns occurred on the fifteenth January, 1934, because of Bihar-Nepal quake, which was in charge of far reaching annihilation however not of equivalent size to that accomplished in 1899.

Table 1 Major Landslide in Darjeeling Hill Region YEAR BLOCK/MUNIPALITY AREA 1998 Kurseong Tindharia T. E 1999 Kurseong Sittong III & I GP Tindharia Sukhia pokhari Pusumbing Relling Basty Hathale Basty Darjeeling sadar Botanical Garden 2000 Jaear Basty Kurseong Sepoydhura Darjeeling sadar Dali Harishatta 2001 Kurseong Rohini 2002 Kurseong 2003 2004 Sukhia pokhari Mim T. E 2007 Kalimpong Monsoon 2016 Bengal Bengal 2017 Cooch Behar North Bengal

On this event, the best layers of the sub-soil on the peak of the Darjiling edge and its remote goads, for the most part on the western side of the town, created gaps harming structures. Between the eleventh and thirteenth June, 1950, the slope inclines in and around Darjiling, Kurseong, and Kalimpong towns were severely influenced by a progression of avalanches after an overwhelming spell of rain of 834.10mm making far reaching harms streets, railroads, houses and open works. 127 individuals were slaughtered and a few hundreds http://rcin.org.pl 40 Subhash Rajan Basu and Sunil Kumar De were rendered destitute. The -Kalimpong railroad line was shut everlastingly, as the slopes in that district were viewed as perilous for railroads. Every one of these occasions pale into irrelevance in examination with the horrifying catastrophe, which overwhelmed Darjiling- Himalayas late in 1968.

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Figure 1 Darjiling critical area zonation Because of relentless and substantial rain of 1121.40mm in the vicinity of third and fifth October,1968 there were various landslides joined by phenomenal surges in the Tista and different rivers. Hill and NH 31 were totally washed away. A few bridges at strategic points (The Rongpo connect on the Sikkim outskirt, a one traverse solid scaffold at Tistabazaar (market), the Railway connect at Sevok and a few others) were either washed away or seriously harmed. The loss of life, formally evaluated was 677 while informal reports put the figure significantly higher. The landslides at Giddapahar close Kurseong, harmed more than 175m of street and railroad track and crushed numerous bustee (slum) villas.

Table 2 Statistical Data of Earthquakes in

Date of Location Position Magnitude Description Occurence 23 June 1976 South of the 21.180 N, Mb 5.0 (4), This earthquake was located in the Bay Sunderbans, West 88.620 E D=050.0 kms, of Bengal off the Ganga Delta. Bengal OT=15:38:42 19 Gangtok area, 27.400 N, Ms 6.1 8 people injured and damage in November Sikkim 88.800 E (4),D=047.0 kms, Gangtok. Felt throughout eastern India, 1980 OT=19:00:45 Bangladesh, Bhutan and Nepal (7). 26 March Chingrakhali- 21.180 N, Mb 4.9 This earthquake was located along the 1981 Bhairabnagararea, 88.620 E (4),OT=02:47:10 India-Bangladesh border to the east of West Bengal Canning, West Bengal. 12 June 1989 Sunderbans, 21.861 N, Mw 5.7 (7), 1 person was killed and 100 injured in Bangladesh 89.763 E D=006.0 kms, the Banaripara area of Bangladesh. Felt OT=00:04:09 in much of eastern Bangladesh including at Chittagong and Rangpur. It was also felt in Meghalaya, India. 28 Ganga Canyon, 21.015 N, Mb 4.7,D=010.0 A light earthquake occurred in the November South of the 89.158 E kms, OT=16:57:13Ganga Canyon in the northern Bay of 2005 Sunderbans Bengal, off the Sunderbans on 28 November 2005 at 22:27 PM local time in India. The earthquake had a magnitude of Mb=4.7 and was felt in southern parts of West Bengal.

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Acronyms Used: D = Depth, OT = Origin Time, Mw = Moment Magnitude, Ms = Surface Wave magnitude, Mb = Body Wave Magnitude, ML = Local Magnitude, M? = Magnitude Type unknown.

Figure 2 Map showing the earthquake report

Figure 3 Lithology map of darjiling All the highways and road ways in Kalimpong town were seriously affected and numerous houses fallen because of land subsidence. As indicated by the Indian Tea Association, 10-15 percent of the aggregate tea zone in the Darjiling Himalaya was decimated together with the loss of 100 lives and across the board harm to production line structures and different establishments. During third and fourth September 1980, because of overwhelming precipitation of 299.1mm Rimbik, Lodhama, Bijanbari, Darjiling town, Sukhiapokri, Manebanjan, , Tindharia, Happy Valley, and (Kurseong) were influenced by extreme landslides, executing 215 individuals and decimating properties worth around 100

http://iaeme.com/Home/journal/IJCIET 58 [email protected] S. RinaMaiti and Dr. L. Mishra million rupees. 462.5 mm of overwhelming precipitation during 15 and sixteenth September 1991 made various landslides in and around Darjiling town, Ging, Tukvor, Bennockburn, Bloomfield tea patio nurseries and Paglajhora and Chunabhati regions executing 2 individuals and disjoining the railroad association amongst slopes and fields. It took very nearly 5 months to re-establish the railroad association amongst Darjiling and Siliguri. In 1993 due to the incident of heavy and concentrated rainfall of 211.3 mm during eleventh to thirteenth July, endless landslides crushed Mangpoo, , Pesoke, Rangtong, Tindharia, Pankhabari, Mahanadi, Gayabaari, Ambootia, and Darjiling towns. 15 individuals were slaughtered in Mangpoo alone, and harm to properties was very high. The long periods of 1995,1998, 2001, 2002 and 2003 saw the most recent instances of landslips in Darjiling town and along the Hill-Cart street from Kurseong to Darjiling. Because of high precipitation (300 - 600 mm) on the fifth - seventh July 1998, the release of the considerable number of streams expanded so enormously that they cut the toe of the Hill-Cart street, causing various avalanches, toe-disintegration and subsidence. Landslide Material: The type of landslide that occurs in a given location often depends on the composition and type of material which form the ground near the surface.

Table 3 Relationship between types of movement and the types of material TYPES OF MATERIAL TYPES OF MOVEMENT Bedrock Soils Coarse Grained Soil Fine Grained Soil Falls Rock fall Debris fall Earth fall Toppes Rock topple Debris topple Earth topple Slides Rotational Rock slide Debris slide Earth slide Translational Lateral spreads Rock spread Debris spread Earth spread Flows Rock flow Debris flow Earth flow Complex: Combination of two or more types of movement

Table 4 Area under different soil erosion Classes Erosion Classes Darjeeling Jalpaiguri Koch Bihar Area (ha) Area % None to slight erosion - 41811 3729 45540 55.58 Slight erosion - 17 2731 2748 3.32 Slight to Moderate erosion 28 23709 438 24175 29.5 Moderate erosion - 8670 0 8670 10.58 Misc. - 793 22 815 0.99 Total 28 75000 6920 81948 100

Table 5 Erosion Class EROSION Darjeeling Jalpaiguri Coochbihar Total area %area

None to slight erosion 1032 59112 20609 80753 36.35 Slight erosion 35645 213 - 35858 16.14 Slight to Moderate erosion 22366 14867 - 37233 16.76 Moderate erosion 23791 13314 3255 40360 18.17 Moderate to Severe erosion 2307 683 - 2990 1.35 Severe erosion 445 511 - 956 0.43 Severe to Very severe erosion 49 - - 49 0.02 Miscellaneous 2804 18560 2594 23958 10.78 Total 88439 107260 26458 222157 100.00

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Figure 4 Average Temperature Graph of Darjiling The qualities of the geography are the principle factors controlling the profundity and style of avalanche disappointments in all the areas considered. In Table. below, the profundity of sliding and the edge of the slant of the 64 avalanches are isolated into three classifications. It can be seen that the basic profundity of most of the avalanches is 5– 15 m and they happened where the slant points were in the request of20–45 o. Profound seated multiple rotational developments stretching out to profundities of more than 15 m represent just 18.7% of the aggregate. Slope instabilities with a profundity of sliding of under 5 m are considered to be shallow. Where the incline edge surpasses 45o, most instances of precariousness were as falls and topples.

Table 6 Summary of depth of sliding and angle of slope in the 64 studied landslides Parameter Category (m) Number of cases % from total Remark Depth of sliding <5 5 7.8 Shallow 5-15 47 73.5 Deep >15 12 18.7 Very Deep Slope angle <20 7 11 Gentle 20-45 51 79.6 Steep >45 6 9.4 Very Steep

5. CORRELATION OF LANDSLIDES AND RAINFALL Another critical point is that most landslides occurred in territories where the incline angle is in the vicinity of 20 and 457.Displaced soil masses examined from semi-round slant failures were generally homogeneous with high dirt substance. Those landslides with a normal profundity of sliding of under 5 m are thought to be shallow and the most incessant basic profundity in profound avalanches was 5– 15 when day by day precipitation was not as much as somewhere in the range of 5 mm, its impact on soil dampness variety and the advancement of pore weights both in the dry and blustery seasons is accepted to be irrelevant as it is likely that it vanishes rapidly. In view of this proof and disregarding instances of shake falls and shake topples which include various diverse components, the accompanying condition is proposed to decide the impact of precipitation on slope slant precariousness in Ethiopian highlands:        

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Figure 5 A rotational landslide that has evolved into an earth flow (parts of a landslide)

6. LANDSLIDES PREVENTION METHOD & FLUX SENSOR Landslides are one of the significant calamities that happen in hilly district. They are eccentric by nature and in this way their analysis is complex to contemplate. RS and GIS tools can be of most extreme significance in dissecting the impact of components on which the event of a landslide incident depends. The meaning of "Landslide Hazard Map" incorporates "zonation indicating yearly probability of landslide happening all through a region" (USGS). A landslide powerlessness outline an essential idea of landslide susceptibility (Radbruch 1970; Dobrovolny 1971; Brabb and Pampeyan 1972) incorporates the spatial distribution of variables identified with the precariousness forms so as to decide zones of landslide-inclined zones with no transient implication. This approach is valuable for regions where it is hard to sufficiently secure data concerning the verifiable record of landslide occasions positions the incline solidness of a territory in classes that range from stable to insecure. Susceptibility maps demonstrate where landslides may happen.

Temperature Buzzer sensor

ARDUINO APR Module UNO

Flux sensor UART GPS

Force sensor GSM

Figure 6 Block of Landslide Monitoring To start with the goal of the investigation is defined. Danger exists that the information that will be gathered will not be as per the size of analysis, or the technique for analysis. This may prompt an exercise in futility and cash if excessively point by point information is gathered, or an oversimplification if excessively broad information is gathered.

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The following things should be considered  The objective of the study  The scale of the study  The type of analysis that will be followed  The types of input data that will be collected

Landslide hazard studies can be made for many different purposes. Some of these might be  For an environmental impact study for engineering works;  For the disaster management of a town or city;  For the modeling of sediment yield in a catchment;  For a watershed management project;  For a community participation project in disaster management;  For the generation of awareness among decision makers;  For scientific purposes Each of the above objectives will lead to specific requirements with respect to the scale of work, the method of analysis and the type and detail of input data to be collected

Scales of Analysis National scale: Smaller than 1:1.000.000, covering an entire country, mainly intended to generate awareness among decision makers and the general public. Maps on this scale are often intended to be included in national atlases. Regional scale: Between 1:100.000 and 1:1.000.000, covering a large catchment area, or a political entity of the country. The maps at this scale are mostly intended for observation phases for planning projects for the construction of infrastructural works, or agricultural development projects. Medium scale: Between 1:25.000 and 1:100.000, covering a municipality or smaller catchment area. Intended for the detailed planning phases of projects for the construction of infrastructural works, environmental impact assessment and municipal planning Large scale: Between 1:2.000 and 1:25.000, covering a town or (part of) a city .They are used for disaster prevention and generation of risk maps, as well as for the design phase of engineering works. Site investigation scale: Between 1:200 to 1:2000 covering the zone where engineering works will be completed, or covering a solitary landslide. They are utilized for the definite outline of designing works, for example, streets, spans, passages, dams, and for the development of incline stabilization works.

Flux Sensor The sensor called the temperature sensor which is utilized to decide the change in temperature and the flux sensor decides the vibration of the field where the threshold is around 1000 and the force sensor decides the stickiness and weight of the ecological conditions. At the point when the threshold value of the flux sensor achieves the range of 700 then it tells the event of the landslide and through the APR module which is the voice module used

http://iaeme.com/Home/journal/IJCIET 62 [email protected] S. RinaMaiti and Dr. L. Mishra to alarm the close-by individuals through a recorded voice. The ringer which is put over yonder used to alarm the vehicle passers who are going out and about. These data are exchanged through the IOT which goes about as a cloud to store the data accordingly.

Figure 7 Slope Alarm system

Figure 8 Sensor set up on surface

(a) Test bed (b) Sensor connections Figure 9 View of test bed for laboratory trial

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In-place inclinometer Tiltmeter sensor

Figure 10 View of sensor installed at test bed

7. FIELD DEPLOYMENT The existing infrastructure evolved through several iterative phases in its implementation. Important research focal points were deciding the sensor locations, designing and constructing the sensors, sensor deployment methods, interfacing circuitry, wireless sensor network and power solutions regarding soil tests and data analysis.Extensive field investigations were conducted for identifying the possible locations for sensor deployment. After analyzing the parameters of the soil and finding the frequently occurring landslide area, the sensors are placed in that place to determine the landslide possibilities. If the soil displacement occurs in accordance with the change in temperature and pressure due to environmental conditions the sensor called flux sensor placed in the field sense the vibration in the area. If the landslide is going to occur an IOT is used in order to transfer the data through GPS.

8. DEPLOYMENT OF SENSOR, WSN & IOT One of the sensors is sent at the toe area where different water drainage lines focalize. This reality is prompt the establishment of pore pressure sensors at various profundities of the sensor section. Both the motion sensor and power sensor are inspected at like clockwork. The remote sensor hub is associated with the sensor segment which transmits the digitized information esteems to the upper layer of the network. The other sensor is appended with the development of joined with development sensors since its area is an unsteady region. This sensor segment is utilized to catch the development of the earth from the sensor segment bending. The remote sensor hubs test these sensors at consistently and sent to upper level hubs in the network. The design and development of a remote sensor organize for the landslide situation includes consideration of various factors, for example, landscape structure, vegetation list, atmosphere variety, availability of the region. The requirements of remote sensor organize improvement are determination of sensor area, sensor segment outline and its information gathering strategy, understanding transmission range and need of outer elements or extra hubs, recognizable proof of the communication protocol. The sensor segment is physically connected to a remote sensor hub which is coordinated with an information procurement board. The IOT is utilized to exchange the information from the portal and it utilizes outer hubs to the entrance point for the same. Since the southern locale encounters visit landslides and has a few landslide inclined regions inside each meter which can be used as future expansion by means of IOT.

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Monitoring The framework comprises of the data base server and an examination station utilizing the product called proteus which has the ability to decide the factor of genuine spilling of data and its outcome over internet which will give the more prominent capacity of viable cautioning issues at minimum delay. It likewise has the capacity to look at and investigate the estimation of various sensors for the correlation. At that point the data is effectively gotten from the deployment site.

Warning Systems  Potential measures include  Landowner education on natural warning signs and self evacuation  Low Level Early warning systems  Regular monitoring and assessment of risk areas by qualified staff  Active monitoring of rainfall forecasts and radar during events to detect any potential issues  High Level Early warning systems - Low Level Early warning systems plus  Forwarding of all severe weather warnings to residents in risk areas (email and text alert)  Deployment of mobile radar to monitor areas of concern during major events  Rainfall sensors in all catchments

Figure 11 A simple tree structure on landslide assessment

9. CONCLUSION AND FUTURE WORK Wireless sensor network for landslide detection is one of the testing research zones accessible today in the field of geophysical research. This paper depicts around a real field deployment of a remote sensor network for landslide identification. This framework utilizes heterogeneous network made out of remote sensor hub and IOT terminals for proficient conveyance of continuous data to the data management focus. The data management focus is furnished with Software's and Hardware's required for complex analysis of the data. The consequences of the examination as landslide alerts and hazard appraisals will be given to the

http://iaeme.com/Home/journal/IJCIET 65 [email protected] GIS and Sensor Based Rain Water Harvesting with Artificial Intelligence System for Free Landsliding occupants of the locale. The pilot deployment of this framework is as of now set up future, this work will be stretched out to a full deployment with expanded spatial fluctuation and the work in such manner is advancing. Field experiments will be directed to decide the impacts of thickness of the hubs, vegetation, area of sensor segments and so forth,to detect precipitation initiated landslides, which may help in the development of low cost remote sensor network for landslide recognition.

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