Kaziranga Sensor Report - May 2017

RAPID ASSESSMENT TO EVALUATE THE EFFICACY OF AUTOMATED ANIMAL SENSOR SYSTEM INSTALLED ON NATIONAL HIGHWAY 37 AT KANCHANJURI-BURAPAHAR CORRIDOR KAZIRANGA TIGER RESERVE

May 2017

Rapid Assessment to Evaluate the Efficacy of Automated Animal Sensor System Installed on National Highway 37 at Kanchanjuri-Burapahar Corridor, Kaziranga Tiger Reserve Wildlife Institute of India Dr. V. B. Mathur Dr. Asha Rajvanshi Dr. Bilal Habib Ms. Akanksha Saxena Mr. Adrian W. Lyngdoh

Kaziranga Tiger Reserve Dr. Satyendra Singh

Contents S. NO. I

DETAILS Background National Highway 37: A Major Threat to Wildlife II Species and Habitat Integrity Review of Mitigation Measures Proposed for III Maintaining the Functionality of Wildlife Corridors in the KNP-KA Hill Complex IV Installation of Automated Animal Sensor System Functioning of the Automated Animal Sensor V System VI Monitoring Sensor Efficacy on Ground VII Observations and Suggestions References Appendix – I: List of People Consulted during the Survey

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I.

BACKGROUND

The Kaziranga-Karbi Anglong Landscape The forests from Bokaghat in the East to Jakhalabandha in the West up to the Brahmaputra River were ideal habitat for a wide variety of wildlife in Assam. Owing to human settlements and increasing development pressures, the biodiversity of the region is now restricted to the Kaziranga-Karbi Anglong landscape consisting of the Kaziranga National Park (KNP) and the Karbi-Anglong (KA) hill complex.

The KNP is now the largest integrated unit of the Brahmaputra valley flood plain grassland ecosystem complex.

The KNP today, holds the largest population of the endangered greater one-horned rhinoceros, which once ranged across the Indo-Gangetic plain. Other mammals that make up the ‘great five’ of the landscape include the swamp deer, Asian elephant, tiger and wild buffalo. At the same time, commercial felling, encroachment for settlements and cultivation, short-cycle jhum cultivation in the hill slopes, overgrazing, extension of infrastructure facilities and various development activities pose a serious challenge for the conservation of the biodiversity of this landscape in Assam. More significant among developmental activities that threaten the integrity of the landscape and negate conservation efforts is NH 37 that cuts across several vital ecological corridors. With the current trend of infrastructure development, the Park is at risk of becoming an ‘island’ in a sea of development (Mathur et al., 2005).

Lying to the south of the KNP, separated by National Highway 37, is the Karbi-Anglong hill complex that consists of the North KA Wildlife Sanctuary (proposed) and the East KA Wildlife Sanctuary (Figure 1).

The KA hill complex is vital for the KNP and the Kaziranga-Karbi Anglong Elephant Reserve as it provides shelter to the animals migrating from the Park during seasonal flooding of the grasslands. The East and North KA Wildlife Sanctuaries together constitute the 16th Important Bird Area (IBA) of Assam.

Seasonal migration in KNP The Park experiences annual flooding of the grasslands because of the high flood waters of the Brahmaputra River coupled with heavy showers in the southern KA hills. This natural event rejuvenates nutrients of the grasslands and beels, and flushes out water hyacinth from waterways. Because of the annual flooding, animals migrate from the Park to the high lands of the KA hills through corridors. This movement occurs during the rainy season (June-August) and may extend until September or October (Bonal and Choudhury, 2004).

These corridors are, however, compromised because of increasing anthropogenic pressure in the form of human settlements, industrial growth and road development. The permeability of corridors varies for different groups of animals (Rajvanshi et al., 2013). Human settlements on both sides of the highway on certain stretches further restrict animal movement across these corridors, leading to increasing conflict between migrating animals and humans.

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Figure 1: Satellite image of the Kaziranga-Karbi Anglong landscape.

Fully soaked a herd of elephants cross the highway in the early hours of morning when the traffic is not too bad.

Later in the day traffic on the highway causes a lot of stress to tired animals that jump back into the flood-waters unable to cross the highway due to constant traffic.

Page 2 of 34 Pic: Sandesh Kadur

II.

NATIONAL HIGHWAY 37: A MAJOR THREAT TO WILDLIFE SPECIES AND HABITAT INTEGRITY

National Highway (NH) 37 starting from Sutarakandi near Karimganj in Assam and terminating at Bhali in Manipur is the only road link connecting the whole of upper Assam to the states of Nagaland and southeastern Arunachal Pradesh with the rest of the country. NH 37 cuts through the southern boundary of the KNP, severing the connectivity of five remaining vital corridors that provide passage to animals fleeing out of the low-lying flooded grasslands of KNP to the high grounds of KA hills. During this flooding, many animals are killed because of collisions with vehicles on the highway. In the nonmonsoon periods too wildlife mortalities occur when general animal movement between the KNP and KA hills encounter NH 37 on the way.

A total of 448 animals have died as a result of collisions with vehicles on the highway in the period 1998-2014 (Bonal and Choudhury, 2004; Eastern Assam Wildlife Division, 2013; Government of Assam, 2015; Assam Forest Department Records). Hog deer are most vulnerable to roadkill (236 kills in 17 years), while primates (capped langur, macaque sp. and Hoolock gibbon) and reptiles suffer high mortalities.

These collisions occur in two seasonal time-frames: one during the monsoon (June-August and may extend to September/October) when annual flooding of the grasslands occurs as a result of which animals migrate towards the KA hills. Mortalities occurring during this period constitute a substantial part of all road-related wild animal mortalities the NH 37 (Figure 2). The second timeframe of mortalities occurs during the rest of the year when natural animal movement between the KNP and KA hills causes them to encounter the highway.

100% 90% 80% 70%

60% 50% 40% 30% 20% 10% 0% 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Monsoon

Non-monsoon

Figure 2: Season-wise (monsoon vs. non-monsoon) wildlife mortality on NH 37

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III.

REVIEW OF MITIGATION MEASURES PROPOSED FOR MAINTAINING THE FUNCTIONALITY OF WILDLIFE CORRIDORS IN THE KNP-KA HILL COMPLEX

The Ministry of Environment and Forests granted conditional environmental clearance to Numaligarh Refinery Limited for setting up its refinery project in district Golaghat, Assam through OM dated 31st May 1991. One of the conditions relates to de-notification of the stretch of NH 37 from Jakhalabandha to Bokakhat and the diversion of the Highway away from Kaziranga National Park (KNP) before the commissioning of Numaligarh project. The project was commissioned in the year 2000, but adequate measures related to NH 37 were not implemented and therefore an application under section 14 and 15 of the National Green Tribunal Act 2010 was filed by Shri. Rohit Choudhury (Applicant – Application No. 174 of 2013).

In response to the directives of Hon'ble National Green Tribunal (NGT), the Government of Assam submitted a proposal for long-term measures to be undertaken for protection of Wildlife: “Suggested strategies to overcome the barrier effect of National Highway 37 on the Wildlife of Kaziranga National Park: a feasibility report”. The report identified potential animal corridors, and outlined short and longterm measures that have been or are to be implemented to control wild animal mortalities on the highway.

Subsequently, WII (2014) reviewed the mitigation measures proposed by the state government in the report viz., crossing structures, their locations, design, suitability, and proposed additional measures to reduce the impacts of the highway on wildlife.

Consequently, in response to an application (No. 174 of 2013), the National Green Tribunal (NGT) vide order dated 13th January 2015 in the MA 142/2012 directed the State Government of Assam to ensure fixation of sensor operated automatic barriers at the animal corridors i.e., the points where as per survey already done the animals cross the highway to reach the other side of the forest area.

Following the order, a report entitled “Brief report on immediate and short-term measures for arresting accidents and killing of wildlife on the NH 37 corridors of the World Heritage Site Kaziranga National Park” (Government of Assam, 2015) was submitted. The report outlined the compliance statement on the directives of the Hon’ble NGT. It presented an overview of animal sensor technologies available and being used in western countries, and the effectiveness and suitability of such measures in the Kaziranga landscape. The report then explored possible technologies that would be suitable to the landscape. One of such technological alternatives is the installation of Automated Animal Sensor System.

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IV.

INSTALLATION OF AUTOMATED ANIMAL SENSOR SYSTEM

i.

Automated Animal Sensor System

The automated animal sensor barrier system is the first of its kind to be implemented anywhere in the India. It is designed to manage wildlife vehicle collisions on NH37. It consists of 2 thermal sensors employed at diagonally opposite sides of the road at each end of the sensor-barrier system to detect animal movement. These sensors are directed towards the road verges for early detection of wild animals moving towards the road. The acquired information is then relayed to the control room and to the traffic barrier for managing the traffic accordingly. The system also has a set of 12 optical cameras that are used for visual interpretation of the thermal images as well as overseeing the traffic movement on the highway. Figure 3 depicts the arrangement of these various components of the system. Table 1 describes the technologies implemented and their salient features.

Figure 3: Arrangement of the sensors and traffic barriers of the Automated Animal Sensor System in NH37

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Table 1: Components of the Automated Animal Sensor System and their utilities Component Thermal camera (2) Optical camera (12)

Brand/Model Mobotix MX-M15TR079 Dahua – HFW5421

Utility Salient Features Thermal imaging to detect Includes thermal radiometry; animal movement dual lens with optical lens.

Vari-focal lens from 5 mm to Capture of video 50 mm Signaling and control of 2 RED-AMBER traffic lights vehicle movement with traffic barrier Provide information for vehicles Has battery bank, UPS and Provide solar and wind inverter, 6 solar panels and power to equipment 9 Vertical Axis Wind Turbines.

Traffic controller

Custom make

Electronic signages

Custom make

Solar panel-wind turbine hybrid system

Windstream Technologies – SolarMill

Video analytics and video management software (VMS)

Mirasys NVR Enterprise

Video management and video analytics

Storage/ server and PC

Custom built server + GNAP NAS

Network switches

Multiple brands

Lightning arrestor

Custom make

Control room with 4 display panels

Samsung 40” display panels

For installation of VMS, sensor software and recording of data For communication between different IP based equipment Protection of equipment from lightning Display of video and control software

Continuous recording with one month storage capacity NAS based storage

Mounted above tree height

1): The thermal camera (Figure 5) has a thermal image sensor and an optical image sensor. The specifications of the camera are listed in table 2 below.

MX sensor module (Color/Black & white), optional)

Thermal image sensor

Figure 5: Thermal imaging camera with a thermal sensor and an optical image sensor

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Table 2: Technical specifications of the thermal camera Model Lens options Thermal image sensor (right) Lens options MX sensor module (left, optional) Sensitivity Thermal image sensor (right) Temp. measuring range Thermal image sensor (right) Sensitivity MX sensor module (left) Image sensor Thermal image sensor (right) Image sensor MX sensor module (left) Max. image size Thermal image sensor (right) Max. image size MX sensor module (left) Image formats Thermal image sensor (right) MX sensor module Max. frame rate Thermal image sensor (right) Max. frame rate MxPEG (Live/recording with sound) MX sensor module (left) Image compression Internal DVR External video ring buffer Software (included) Image Processing

Virtual PTZ Alarm/events

Microphone and speaker

MX-M15D-Thermal-L135 135:17° horizontal field of view 180° to 13° horizontal field of view NETD typ. 50 mK (equals 0.05°C), <79 mK, IR range 7.5 to 13.5 μm –40 to +550°C/–40 to 1,022°F Color sensor: 0.25 Lux at 1/60 s, 0.013 Lux at 1 s black & white sensor: 0.05 Lux at 1/60 s,0.0025 Lux at 1 s, MxLEO – MOBOTIX Lowlight Exposure Optimization Uncooled micro bolometer, 336x252 pixels 1/2.5“CMOS, 5 MP (2592x1944 pixels), progressive scan Can be scaled up to 2048x1536 (QXGA), automatically scaled to size of MX sensor module Color/Black & White 2048x1536 (QXGA) 2048x1536 (QXGA), 1920x1080 (Full HD), 1280x960 (MEGA), 1280x720 (HD), 1024x768, 800x600, 768x576 (D1-PAL), 704x576 (TV-PAL), 640x480, 384x288, 320x240, 160x120, custom formats 9 fps* VGA: 30 fps, MEGA: 30 fps, QXGA: 20 fps, Dual image: 9 fps MxPEG, M-JPEG, JPEG, H.264 (SIP video only) MicroSD slot including 4 GB, max. 64 GB Up to 4 TB directly on NAS and PC/Server, no additional recording software required MxEasy video management software, MxControlCenter control center software, MOBOTIX App for iOS devices version 5.0 and higher Backlight compensation, automatic whitebalance, image distortion correction, panoramacorrection, video sensors (video motion detection/MxActivitySensor), optional off-color/black &white display of thermographic sensor Digital pan/tilt/zoom, continuous up to 8X Video Motion detection, MxActivitySensor, externalsignals, temperature sensor, PIR, microphone,shock detector, notification via e-mail, FTP, IPtelephony (VoIP, SIP), visual/acoustic alarms, pre- andpost-alarm images Microphone and speaker integrated Page 7 of 34

2): Specifications for the optical cameras (Figure 6) are provided in table 3 below.

Figure 6: Optical camera Table 3: Brief technical specifications of the optical cameras used for the system Camera Image Sensor Effective Pixels Scanning System Minimum Illumination IR Distance Day/Night Noise reduction Lens Focal length Max. aperture Angle of view Video Resolution

Frame rate Audio Compression

Main stream Sub stream Third stream

1/3” 4 mega-pixel progressive scan CMOS 2688 (H) x 1520 (V) Progressive 0.01Lux/F1.4 (Colour), 0 Lux/F1.4 (IR on) Up to 50 m Auto (ICR)/ Colour/ B/W 3D 2.7~12 mm F1.4 H: 100°~33° 4M(2688×1520)/3M(2304×1296)/ 1080P(1920×1080)/1.3M(1280x960)/ 720P(1280×720)/D1(704×576/704×480)/ VGA(640×480)/CIF(352×288/352×240) 4M(1~25/30fps) D1(1~25/30fps) 720P(1~25/30fps) G.711a/ G.711Mu/ AAC

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3): The Solar Mill (Figure 7) has a design life of 25 years. It consists of two components viz. the wind component and the solar component. The specifications of these are provided in table 4.

Figure 7: Solar panel-wind turbine hybrid system. It has Maximum Power Point Tracking (MPPT) electronics and solar charge controller, which maximize the power handling and generation capabilities of both the wind turbines and solar panels

Table 4: Technical specifications of the Solar Mill WIND COMPONENT Turbine Related Power Output Wind Component Maximum Power Output Maximum Voltage Maximum Current Rotor Diameter Cut-In Wind Speed Cut-Out Wind Speed Swept Area Turbine Material SOLAR COMPONENT Maximum Power (Pmpp) Voltage at Max Power (Vmpp) Current at Max Power (lmpp) Open Circuit Voltage (Voc) Short Circuit Voltage (Voc) Maximum System Voltage Solar Cells No. of Cells

143 W @ 11 m/s 500 W @ 17 m/s 57 DC 30 Amps 13 in | 0.33 m 4.5 mph | 2 m/s 38.03 mph | 18.5 m/s 1,519 in2 | 0.980 m2 Galvanized G-90 Steel 245 W 30.1 V 8.2 A 37.7 V 8.7 A 1000 V Monocrystalline 60

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ii.

Project Installation Site

The animal sensor with barrier and signals has been installed at the Kanchanjuri-Burapahar corridor that lies in the Bagori range of the KNP near the Maloni anti-poaching camp (Figure 4).

This corridor is highly vulnerable to road-related mortalities of wildlife during the flood season (Bonal and Choudhury, 2004). This is among the relatively undisturbed corridors and is potentially used by animals for movement. It is also under the greatest threat from anthropogenic disturbances as well as from traffic on NH 37 (Rajvanshi et al., 2013).

Figure 4: Site map of the Automated Animal Sensor System in the Kaziranga-KarbiAnglong complex.

The sensor has been set up at Maloni camp in Kanchanjuri corridor under Bagori range iii.

Site visit

An animal sensor system with thermal and optical cameras and barriers with signals have been installed at one corridor along the highway as part of a pilot project. The Wildlife Institute of India as per directions of the NGT and vide Letter No. KNP/FG.733/Sensor/NH-37 dated 7th February 2017 was asked to evaluate the efficacy of the ASS

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V.

FUNCTIONING OF THE AUTOMATED ANIMAL SENSOR SYSTEM

The automated animal sensor system aims to be a holistic and integrated surveillance system designed to control animal mortality on NH 37. It is a combination of thermal and optical cameras installed at different configurations on the road stretch. Figure 8 is a graphical representation of the Automated Animal Sensor System as installed on NH 37 from two aspects- East (towards Kohora, Kaziranga NP) and West (towards Guwahati).

Figure 8: Graphical representation of the automatic animal sensor system- view of animal sensor from East (top) and from West (bottom)

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Figure 9: Driversâ&#x20AC;&#x2122; view of the automatic animal sensor system on NH 37 The entire set-up works in tandem to activate the traffic lights, LED signage and boom barriers located at the two ends of the road stretch (Figure 10).

Figure 10: Boom barrier, LED display and traffic lights located at both ends of the sensor set-up The detector circuit that has an infrared camera on both sides of the road stretch is designed to detect the presence and movement of an animal about to cross the road. A passive infrared sensor (pirsensor) is an electronic sensor that measures infrared (ic) light radiating from objects in its field-of-view.

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They are most often used in pir-based motion detectors. Here it is used to detect the presence of an animal (Figure 11).

Figure 11: Thermal cameras set up with optical cameras to detect animal movement Twelve optical cameras have been placed in the entire sensor set-up- 4 each with each thermal camera and 4 stand-alone optical cameras (Figure 12). The purpose of the optical cameras placed with the thermal cameras is to provide reference to the thermal images seen through the thermal cameras for confirmation by the human operators. At night however the optical cameras are unable to provide any clear feed except when a source of light (headlights of oncoming vehicles) is present. The 4 standalone optical cameras have been installed as part of the Automatic Number Plate Registration (ANPR) system which is not functional during the period of the survey.

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Figure 12: Two of the four stand-alone optical cameras that are to be used as part of the ANPR system The detector circuit as shown in Figure 13 communicates the information to the control unit as shown in Figure 14 by means of short range communication. The controller section comprising of a microprocessor or micro controller manages the traffic according to the signal received, by showing a red or stop signal on both sides of the set-up. Once the animal has crossed the road the controller gives a signal for the barriers to be lifted. (The components in blue boxes in both the figures are those that havenâ&#x20AC;&#x2122;t been installed/activated on the system yet.)

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Figure 13: Block diagram of the sensor module with all the sensors and devices required attached to it

Figure 14: Block diagram of the actuator module with all the devices (actuators) required attached to it Zigbee is a specification for a suite of high level communication protocols using small, low power digital radios for a personal area network. It is used to send information to the traffic module about the status of the roadside. The control room for the sensor is located within the Maloni anti-poaching camp (Figure 15).

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Figure 15: Control room of the animal sensor system where video imagery is displayed If an animal stays on the road for long, an alert SMS would be sent to forest officials through GSM (a warning system composed of a buzzer and flashlight to make the animal move) was proposed by the proponents, but has not been installed. It is planned that using GSM-based alerts, the forest officials can be informed of the system operations. The entire process proposed is explained in a flowchart in Figure 16.

The whole system is powered by solar and wind energy (Figure 17) since providing traditional wired power is not feasible in the project site.

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Figure 16: Flowchart of the entire system showing the sequence of events during and after triggering of the sensor. The highlighted portion of the process is not functional

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Figure 17: Solar and wind power panels at the project site The video analytics and video management is being done through Mirasys NVR Enterprise software. It is designed to manage and analyse multiple cameras as a single system independent of location. The software records the videos from multiple analog and IP cameras. The software supports multiple recording modes (continuous, motion-based and event-triggered) and has an advanced motiondetection. This is supported by a user interface on monitors located in the control room in which the user can choose IP cameras for live view monitoring, recording and playback (Figure 18).

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Figure 18: View of the user interface where feed from all optical cameras are viewed in the control room

Page 19 of 34 Pic: Bilal Habib

VI. i.

MONITORING SENSOR EFFICACY ON GROUND Methods and Observations

A team of researchers from WII subsequently visited the project site to monitor the project from 3rd – 11th March 2017.

The thermal cameras are the only primary sensors used for automatic detection and relaying of information to the control room. Optical cameras do not have such automatic capabilities. Thus, only the detection capability of the thermal cameras was tested.

The field of view (FOV) of the thermal cameras has been divided into three segments as seen in Figure 19. For example, for thermal camera number 13, the right-most part of the FOV detects animal movement and alerts the system. When the animal walks past the 90° mark of the FOV, the dot on the top right corner of the screen turns red and the alarm gets triggered. As the animal approaches the third segment, the trigger for lowering of the barrier is set off.

Figure 19: Thermal image of camera 13 showing three segments of the camera’s FOV We tested the effectiveness of the thermal cameras on both ends of the animal sensor set-up with the following objectives: Page 20 of 34

a.

To determine the maximum and minimum distances of thermal cameras under different light and vegetation conditions at which the system detected animals, showed the alert sign and then set-off the alarm.

b.

To determine conditions under which false positive and false negative triggers were set off.

c.

To observe the general working of the sensor system.

ii.

Testing of thermal cameras:

There are two thermal sensors (camera 13 and 14) placed at the opposite ends of the Automated Animal Sensor System. For the purpose of this experiment, both the sensors were calibrated to detect a cow and to set the alarm off whenever the cow comes within the field-of-view (FOV) of the sensor.

For safety reasons, the boom barrier was disconnected from the sensor system. Only the traffic signals functioned. The sensors were tested between 2:30 pm and 6:00 pm. The cameraâ&#x20AC;&#x2122;s FOV was divided into 3 equal segments from forest towards the road. Vegetation characteristics of the three segments for thermal cameras 13 and 14 are given in Table 5, and can be seen in Figure 20 below.

Table 5: Vegetation cover w.r.t. distance and segment for thermal cameras (Number 13 and 14) Test

CAMERA 13 Segment 1 Segment 2 Segment 3 CAMERA 14 Segment 1 Segment 2 Segment 3

Vegetation Cover Distance from sensor 25 m

50 m

Dense vegetation, trees, shrubs Bare ground Bare ground

Dense vegetation, trees, shrubs Bare ground Bare ground

Tea garden Grass, herbs Grass, herbs

Tea garden Tea garden Dense vegetation, tea garden

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Figure 20: Thermal images of camera 13 (a) and camera 14 (14) showing distance to sensor.

The cow was made to walk at distances of 50 m and 25 m from the sensor. The event was recorded and the videos were then examined. Table 6 shows findings of the experiment.

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Table 6: Observations of the experiment for thermal cameras (Number 13 and 14) TEST

25 m Seg. 2

Seg. 1

Seg. 3

Seg. 1

50 m Seg. 2

Seg. 3

CAMERA 13 D A Al D A Al D A Al D A Al D A Al D A A l Y Y N Y Y N Y Y N N N N Y Y N Y Y N N N N N N N N N N N N N N N N N N N N N N Y Y Y Y Y Y N N N Y Y Y Y Y Y N N N Y Y Y Y Y Y N N N Y Y Y Y Y Y N N N N N N N N N N N N N N N N N N

Cow walking away from road Cow standing in the FOV Cow walking towards road Man walking towards road Dog walking towards road CAMERA 14 Cow walking away from road Y Cow standing in the FOV N Cow walking towards road N Man walking towards road Y Note: D = Detection; A = Alert; Al = Alarm

Y N N Y

N N N N

Y N Y Y

Y N Y Y

N N Y N

N N Y Y

N N Y Y

N N Y Y

N N N N

N N N N

N N N N

N N N N

N N N N

N N N N

N N N N

N N N N

N N N N

Thermal camera 13: During the test, it was observed that camera 13 correctly detected the cow and sent the appropriate message to the control station irrespective of the cowâ&#x20AC;&#x2122;s distance from the sensor. It also ignored presence of other animals such as dogs. However, it also falsely set the alarm off when any human walked towards the road. Figure 21 (a-g) are screenshots of the thermal camera video feed that was taken during testing of the sensor.

Page 23 of 34 Pic: Bilal Habib

(a)

(b)

(c)

(d)

(e)

(g)

(f) Figure 21:Screenshots (a) and (b) show that the sensor could detect the cow and sent an alert to the control station but it did not set off the alarm as the animal was not moving. During (c) and (d) the alarm went off as the cow crossed the 90° angle while moving towards the road. In (e), the cow moved in the direction opposite to the road. The sensor detected the animal but did not set the alarm off. In (f), the dog was ignored by the sensor. In (g), the human walking towards the road was detected and set off a false alarm.

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Thermal camera 14: Camera 14 was unable to detect the cow at distances beyond 50 m. This could be because the cow got partially covered by the tea plants at varying distances distances. At nearer locations where the full profile of the cow was visible, the sensor correctly detected the animal and set off the appropriate signal. The camera detected humans in the frame but did not set off the alarm. The following series of screenshots (Figure 22) of the thermal camera video feed depict testing of thermal camera 14.

(a)

(b)

(c)

(d)

(e) (f) Figure 22: In screenshots (a) and (b), the sensor detected the cow and sent an alert to the control station and set off the alarm. In (c), the cow was too far away for the sensor to detect it. In (d), the sensor detected the cow and sent an alert. It did not set off the alarm as it was not moving(e) in the direction of road. In (f), the person was detected but no alarm was set off.

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iii.

Sensor calibration:

The sensor was calibrated to detect elephants taking into consideration their body dimensions. This was done using domestic elephants (Figure 23). Other wild animals also need to be calibrated for the sensor to detect them appropriately. It has been planned that this will be done opportunistically as and when an animal passes through the corridor. On 19th March 2017, a tiger was apparently captured on thermal camera 13 and the data has been sent to the software company for calibration.

Figure 23: Calibration of the system to detect elephants using domestic elephants iv.

Blind spots:

The thermal cameras are positioned such that their FOV is limited to between a distance of approximately 18 m and 50 m from the sensor (Figure 24). Any animal crossing the corridor within 18 m or beyond 50 m from the sensor will not be detected. In this case, only optical cameras positioned at different points can be used to identify animals visually during day time by personnel stationed at the control room. The alarm system will have to be set off manually as well and is, therefore, not fully automated.

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Figure 24: The ‘blind spot’ area with a radius of 18 m around the thermal sensor The optical cameras will not work at night or will work only if a source of light (light from incoming traffic) is present. As such, there is a ‘blind zone’ of approx. 110 m between the two thermal cameras (Figure 25). Any animal crossing the corridor at night within this blind zone will not be detected by the system.

A reconnaissance of the road stretch within the sensor apparatus reveals that most animal trails lay within these blind spots.

Figure 25: ‘Blind spots’ in the sensor configuration

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v.

Approach to the thermal camera and traffic speed:

The approach to the animal sensor system from both barrier ends starts with a turn. The traffic signal, LED signage and barrier are visible from a distance of 230 m (Guwahati side) and 280 m (Kahora side).

Thus, any vehicle coming from either side of the sensor system may not have enough time to react if the barriers get activated. vi. Energy considerations: There is no electricity provided to the system. It is solely powered by a hybrid system of six solar panels and nine wind turbines which have an overall capacity of 4.0-4.5 kV. The overall storage capacity of the batteries is 6 kV, which can run for 14 hours after full charge. An issue faced by this power system is that there is not enough sunlight or wind speed to charge the batteries to full capacity. a. Wind Power: The wind turbines contribute to about only 2 % of the overall capacity of the batteries.

The turbines have a cut-in wind speed â&#x20AC;&#x201C; the point at which the turbines start generating electricity of 4.5 mph, whereas the average wind speed in Kaziranga is approx. 2 mph with a maximum wind speed of approx. 4.5 mph (Figure 26). These conditions are not conducive to meet the full potential of the wind turbines.

Figure 26: Average year round wind speeds in Kaziranga area (Source: Historical average weather, Data provided by WorldWeatherOnline.com)

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b. Solar power: The efficiency of the solar panels to generate power is reduced during the monsoons when the sky is usually overcast. This further reduces the capacity of the SolarMill to power the animal sensor system.

Figure 27: Average cloud cover (in %) and humidity (in %) in Kaziranga area (Source: Historical average weather, Data provided by WorldWeatherOnline.com)

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VII.

OBSERVATIONS AND SUGGESTIONS

Based on the observations made to access the functional efficacy of AASS the following inferences are drawn and recommendations are accordingly made to improve the functional value of AASS. Observation 1: Detection capabilities of thermal sensor Detection capability of the sensors deteriorates with increasing obstructions present in the FOV. This is because the tea plants obstructed the cameraâ&#x20AC;&#x2122;s view. It was observed during testing, one thermal camera failed to detect the cow beyond a distance of 50 m. Thermal sensors may not be able to detect reptiles and amphibians.

Suggestion: The sensors need to be either placed in areas where there is lesser foliage obstructing the view of the camera or the foliage in the animal trails should be cleared to improve visibility of the camera. The camera should be placed closer to the trail to improve visibility. The performance of the sensor might deteriorate in case of heavy rainfall or in fog conditions.

Observation 2: Activation of alarm and barrier The alarm is activated when an animal reaches the 90 o angle of the thermal sensor. However, there had been instances when there was a delay in activating the alarm.

Suggestion: This needs to be addressed as the animal may be only a few meters away from the road. The threshold line where the alarm is set off should be placed in such a way that it covers the trail that is the most used by animals.

Observation 3: False detection of the sensors Even though the cameras have been calibrated to ignore thermal profiles of cattle, dogs and humans, it was observed during testing that the system showed an alert signal for a human walking 50 m away from the thermal sensor. Detection of animals with dimensions similar to dogs and cows would be an issue leading to false negatives.

Suggestion: Calibration of a larger sample of humans, cattle, dogs, etc. should be done to reduce such false positives.

Observation 4: Calibration of sensor As mentioned in the preceding section, the calibration of the system has to be done individually for all wild mega-fauna in the Kaziranga area that are likely to use the corridor. This would be done as and when an animal is detected in the thermal cameras and the feed data is sent to the software company for calibration. Therefore, the system may not be ready before the start of the monsoon season when the actual migration of wildlife across the corridor occurs and when animal mortality is the highest on the highway.

Suggestion: Opportunistic calibration of the sensor will take a long time and is impractical. Off-site calibration of the thermal sensor set up (for example in a zoo) in a similar configuration should be done for immediate operation of the system in the corridor.

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Observation 5: Blind spots The vertical FOV of the thermal cameras leaves out a circular blind spot beneath the camera pole with a radius of approximately 18 m. Moreover, a substantial area of the stretch of the corridor within the sensor set-up is left out by the thermal sensors because of factors such as limited detection distance of the thermal cameras, non-detection of animals by optical cameras and dense foliage on the roadsides. This implies that human intervention in setting on and off the triggers cannot be ruled out. This is counter-productive to the entire exercise of having a fully-automated ‘sensor’.

Suggestion: To improve the coverage of the sensor system, more thermal cameras need to be placed at strategic positions covering all trails in the corridor.

Observation 6: Activation of boom barrier It is not clear what prompts the system to lift the barriers back. Also, FOVs of the two thermal sensors don’t overlap, so the system of one sensor acting as sender (trigger to lift barrier) when one acts as receiver (trigger to drop barrier) would not work. Hence, automatic activation and deactivation of the boom barrier is not possible and in the event of an animal crossing the road, the trigger to lift the boom barrier would have to be given manually by an operator.

Suggestion: In case of herd-living animals, the trigger mechanism will need to be programmed such that the average herd size of the species is taken into account.

Observation 7: Visibility of sensor-barrier system and risk to commuters Sudden dropping of barriers poses a risk of traffic accidents because the approach leading up to the sensor set-up from both ends of the highway begins with a curve, which may hamper visibility, perception and decision-making by the drivers.

Suggestion: Speed breakers or traffic barricades need to be placed at strategic points on the highway to prevent accidents and reduce risk to commuters.

Observation 8: Viability from energy point-of-view The power provision for the sensor set-up is not enough to keep it live for a long duration. It may pose problems especially during the monsoon season when there may not be enough sunlight to charge the system (cloud cover during monsoon months June-Sept varies between 30-75%). This problem could hamper the efficacy of the sensor system since monsoon is the time when most animal movements occur.

Suggestion: Alternate power sources should be provided for the effective functioning of the animal sensor system.

Observation 9: Cost considerations The cost of the sensor set-up is approximately Rs. 1.25-1.5 crore. The sensor system as we see it today requires human intervention, which would require employment of technologically able personnel, which ultimately will further addto the cost of maintenance of the sensor vis-à-vis its efficiency.

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Observation 10: Constraints in functioning of optical cameras The twelve optical cameras that have been installed for reference work only during the day and sparingly at night given a source of light is present. Optical cameras number 1, 2, 3 and 4 are supposed to be part of the ANPR system. Thus, the ANPR system will not work in the dark (either dusk or dawn).

Observation 11: Maintenance issues Each of these components has different design life after which they will not function effectively.

The harsh conditions in the Kaziranga area will depreciate the life expectancy of these devices than that quoted by the manufacturers. Given the remote location of the sensor set-up, delays in repair and maintenance of the sensor components could be an issue in the future.

Observation 12: Limitations in terms of spatial coverage of sensor The width of corridors connecting KNP with KA hill complex that are intersected by NH 37 span 2-5 km. Alternative sensor configurations should be set up to cover a substantial part of these corridors, since the present sensor spans only 390 m of the 4.4 km wide corridor (including the blind spots).

Observation 13: Replication of such a system in other sites is not desired for the following reasons: 

The present AASS has several limitations both technical and functional that limits its functional efficacy. These need to be adequately addressed now before recommending its use in other areas.



The economics (installation and operational costs) of running several such AASS may not favour the installation of more AASS. This may negate its benefits.



A more robust and better sensor system, functional over large distances may have to be designed, validated and installed at key locations. **********************************

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REFERENCES: Bonal, B.S. and S. Chowdhury. 2004. Evaluation of barrier effect of National Highway 37 onthe wildlife of Kaziranga National Park and suggested strategies and planning forproviding passage. A feasibility report to the Ministry of Environment & Forests,Government of India.

Eastern Assam Wildlife Division. 2013. Suggested strategies to overcome the barrier effect of the National Highway- 37 on the wildlife of Kaziranga National Park: A feasibility report. Divisional Forest Officer, Eastern Assam Wildlife Division. Bokakhat, Assam.

Government of Assam. 2015. Brief report on the immediate and short term measures for arresting accidents and killing of wildlife on the NH 37 corridors of the World Heritage Site Kaziranga National Park. Department of Environment and Forests, Government of Assam.

Mathur, V.B., A. Verma, N. Dudley, S. Stolton, M. Hockings and R. James. 2005. Opportunities and challenges for Kaziranga National Park, Assam over the Next Fifty Years. http://whc.unesco.org/uploads/activities/documents/activity-331-8.pdf. Retrieved 2012-05-28.

Rajvanshi, A., V.B. Mathur and A. Pragatheesh. 2013. Ecological effects of roads through sensitive habitats: Implications for wildlife conservation. Final Project Report. Wildlife Institute of India.

Dehradun.

WII. 2014. Review of the Proposal: Submitted by the Government of Assam in Compliance of the order of the Honâ&#x20AC;&#x2122;ble National Green Tribunal, to suggest Mitigation Measures in the Interest of Wildlife Conservation with respect to National Highway 37. Committee Report Submitted to the National Tiger Conservation Authority.

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APPENDIX I: List of people consulted during the survey S.no.

Name

1.

Dr. Satyendra Singh

2.

Ms. Abharna

3.

Mr. Rohini Ballave Saikia

4.

Mr. Satish Yadav

5.

Mr. Ashok

6.

Mr. Rajesh

7.

Mr. Ravi Shanghati

8.

Mr. Venkat Yechury

Designation Field Director Kaziranga National Park, Assam ACF Kaziranga National Park, Assam DFO Eastern Assam Wildlife Division, Assam Technical Manager Mirasys Software Hardware Technician Vertical Technologies, Hyderabad Engineer Divisys India Private Limited, Hyderabad Project In-charge Divisys India Private Limited, Hyderabad MD Divisys India Private Limited, Hyderabad

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Contact details 9435102834

9577391002

9435130892 9820276773 8008831693

8498055073

9394724000

9822090132

Director Wildlife Institute of India, Chandrabani Dehradun, India 248 001 Tell: 00 91 135 2646102 Fax: 00 91 135 2640117 E-mail: dwii@wii.gov.in

Field Director Kaziranga Tiger Reserve Bokakhat, Golaghat District Assam - 785612 INDIA Tell: 00 91 3776 268095 Email: dir.kaziranganp@gmail.com