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Infralocator (ADPUI) has been developed. This                       studies of Karakoram Himalayas indicate
   utility is capable to read, filter, and process                     warming trends with reduced precipitation
   data for event detection and localisation.                          over the study area.

Acoustic Emission Sensor network installation at Slope site Patsio  • Glacier Thickness Estimation for Geodetic

• Acoustics Emission Snowpack Stability from                           Mass Balance Study: Remote-sensing based
                                                                       ‘Geodetic method’ was implemented to estimate
   Natural Slope site (Patsio): Acoustic Emission                      glacier thickness change and mass balance
   (AE) sensor network has been installed on                           in Karakoram Himalayas, based on DEM
   an avalanche slope site at Patsio (3800 m) in                       generation (Cartosat-1 and ALOS-Prism), and
   order to monitor the continuous AE activity                         SRTM-C DEM. To achieve the accuracy of
   produced during instability development                             generated DEMs, different corrections such
   process within the snowpack. During the                             as planimetric, penetration, curvature, and
   last four consecutive winters, this AE-based                        seasonal were implemented.
   system is installed and is monitoring the
   AE activity in the avalanche slope. Effect of                    HIMSANDESH
   snow-met conditions on AE’s and process of
   instability development was also investigated.                   • Hidden Markov Model (HMM) has been
Assessment of Snowpack Stability over a
Slope using Wireless Sensor Network (AWSN)                             developed for forecasting of snow and
                                                                       meteorological variables and integrated with
     DRDO is involved in the development of                            the avalanche forecasting model to deliver
a comprehensive snowpack stability evaluation                          avalanche warning with a lead time of three days.
system over a slope with ubiquitous network of
wireless sensors. The project will contribute towards               • Nearest Neighbour Model has been developed
providing a state-of-the-art autonomous platform
for acquiring in-situ snow-met parameters and                          using the similar database as used in the
avalanche-occurrence information from avalanche-                       development of HMM. It is based on the
prone mountainous slopes and improving the                             computation of Euclidian distance and ten
accuracy in predicting slope stability. During                         nearest neighbours. It also gives avalanche
the year, a network of 07 nos. geophones,                              warning for 3 days in advance using forecasted
01 no. microphone, and 01 no. 5 MP digital                             snow and meteorological variables.
camera was installed near the avalanche site
to record events of avalanche occurrence in                         • Multivariate Regression model and neural
Jul 2017. Data from all the sensors and images
from the camera are being received wirelessly                          network-based model has been developed
at the Base Station.                                                   for simulation of snowpack parameters such
Impact of Climate Change on Glacier in                                 as snow layer density, shear strength of
Karakoram Himalaya and their Implications                              snowpack layers, snowpack settlement, and
on Army Development (HIMPARIVARTAN)                                    temperature of snowpack layers. The models
                                                                       have been developed using 620 data points
• Climatology of Karakoram Himalayas: Climatological                   extracted from snow stratigraphy. The results
                                                                       of neural network-based model have been
                                                                       found better than that with multivariate
                                                                       regression model.

                                                                    Wheeled Armour Platform (WhAP)

                                                                         WhAP is a multiutility armoured platform
                                                                    with modular design, configurable for a variety
                                                                    of combat and combat-support roles up to 26 T
                                                                    Gross Vehicle Weight (GVW). During the year,
                                                                    User suggestions for design improvements were
                                                                    incorporated in the design of Armoured Prototype-
                                                                    II. Instant Fire Detection and Suppression System
                                                                    (IFDSS) was integrated on AP-II. Upgradation
                                                                    of turret stabiliser system and development

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