Neerav Sharma

@ceew.in

Programme Associate, Sustainable Mobility
Council on Energy Environment and Water

Neerav Sharma


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https://researchid.co/neerav_iitr

EDUCATION

B.E. in Electronics and Communication Engineering [CSVTU, Chhattisgarh]
M.E. in Electronics and Communication Engineering [BIT Mesra]
Ph.D. in Geomatics Engineering [IIT Roorkee]
Post-Doc from Purdue University, USA. [IoT, AI, Sensors]

RESEARCH, TEACHING, or OTHER INTERESTS

Multidisciplinary, Artificial Intelligence, General Earth and Planetary Sciences, Control and Systems Engineering
11

Scopus Publications

335

Scholar Citations

11

Scholar h-index

11

Scholar i10-index

Scopus Publications

  • Satellite-driven assessment of urban pollution susceptibility in West Bengal, India
    Neerav Sharma, Shubham Bhattacharjee, Rahul Dev Garg, Kavita Sharma
    Journal of Environmental Engineering and Science, 2026
    Urban air pollution remains a critical environmental challenge in rapidly developing regions, yet there is a limited understanding of spatial pollution susceptibility integrating multiple atmospheric pollutants and land-use dynamics. This study addresses this gap by developing a geospatial framework to assess pollution susceptibility across West Bengal, India, using Sentinel-5P tropospheric monitoring instrument data for key pollutants, including ultraviolet aerosol, carbon monoxide (CO), nitrogen dioxide (NO2), and formaldehyde (HCHO). A weight of evidence-based modelling approach was employed to integrate pollutant layers and generate a spatially explicit pollution susceptibility map. The results reveal pronounced spatial variability, with high susceptibility observed in northern districts (Uttar Dinajpur, Dakshin Dinajpur, and Maldah), industrial regions (Paschim Bardhaman and Birbhum), and densely populated urban centres such as Kolkata. Land use land cover analysis between 2017 and 2023 indicates a 44.9% increase in urban and 8.06% decline in vegetation, highlighting urban expansion, a key driver of pollution. This study demonstrates that integrating satellite-based pollutant observations with geospatial modelling provides an effective approach for identifying pollution hotspots and understanding their underlying drivers. These findings offer insights for policymakers and urban planners, enabling targeted interventions such as emission control, sustainable urban planning, and continuous monitoring frameworks for improved air quality management.
  • Integrating Fuzzy Logic and Morphological Edge Detection for Enhanced UAV Orthomosaic Mapping
    Pallavi Singh, Nagesh K N, Neerav Sharma
    2025 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation Iatmsi 2025, 2025
    The field of engineering is undergoing continuous advancements aimed at optimizing efficiency and precision. Surveying and mapping, fundamental components of Geomatics engineering, have evolved significantly with the adoption of advanced technologies. Among these, ‘Unmanned Aerial Vehicles (UAVs)’ have been a spotlighted tool for conducting precise and efficient surveying and mapping. This study leverages UAV-acquired data to generate high-resolution point clouds and three-dimensional textured mesh models, forming the basis for Orthomosaic imagery creation. The research highlights critical challenges encountered during the generation and analysis of Orthomosaic images, emphasizing the need for image correction and enhancement to achieve application-level precision in accurate mapping and monitoring. To address these challenges, the study integrates Fuzzy Logic and advanced Edge Detection techniques in image processing to enhance the quality and accuracy of Orthomosaic imagery. The findings provide valuable insights into the methodologies and outcomes of the proposed approach, demonstrating its potential to significantly improve the precision and efficiency of Orthomosaic applications. Furthermore, this research underscores the broader implications for engineering and environmental studies, paving the way for more effective and innovative solutions in these domains.
  • Sustainable management and agriculture resource technology system using remote sensing descriptors and IoT
    Neerav Sharma, Shubham Bhattacharjee, Rahul Dev Garg, Kavita Sharma, Munizzah Salim
    Geomatica, 2024
    The agricultural sector is a paramount arena of research pertaining to both global and Indian context. Despite India's agricultural dominance, productivity has consistently declined due to various factors, leading to economic and farmer losses. This study introduces a dual-approach research deployment aimed at enhancing agricultural management efficiency. The first approach involves utilization of remote sensing descriptors to identify moisture deficit areas using vegetation-moisture indices, land surface temperature and slope-elevation profiles. The descriptors were computed using a ten-year period from 2015–2024 using Sentinel-2 data. The second approach involves the deployment of soil moisture sensors integrated with microcontrollers and IoT infrastructure for real-time monitoring. Soil moisture levels were monitored at real-time during morning, afternoon and evening time-periods with specific thresholds identified for urgent watering and optimum moisture conditions. Data was collected and tested at moisture deficit areas identified by remote sensing descriptors at South and North Roorkee, achieving 97.24 % precision score in real-time alerts. The system developed and portrayed in this research is termed as “SMARTS” (Sustainable Management and Agriculture Resource Technology System) which is scalable and flexible for being deployed at any geographical location offering a robust foundation for future sustainable farming.
  • Hazardous Zone Identification by Spectral Analysis of Ground Penetrating Radar Response
    Udbhav Joshi, , Rahul Dev Garg, Neerav Sharma, Vinod Kumar Joshi, Kavita Sharma, , , , and
    Electrica, 2024
    Abstract: Ground penetrating radar (GPR) has evolved over the years as a profound sensor-based investigation technique operating in a wide range of frequencies ranging from 250 to 1000 MHz and utilizing interaction of electromagnetic waves with subsurface to obtain a pseudo-image of the strata. Often due to constructional negligence and poor standards of construction, the pavement so constructed lacks structural strength and have poor compaction of construction material resulting into air pockets. During rainy season, water seeps into the pavement resulting into settling of sand and gravel underneath the pavement. Hence, when a heavy vehicle crosses over the road patch, it results in subsidence of that patch leading to casualties and property damage. In the present study, a system is developed for classification and identification of hazardous zones on a GPR image that can result in subsidence during rainy season. The system works on extraction of features from GPR response using discrete Fourier Transform. The GPR data collected at two sites in IIT Roorkee campus using 1 GHz antenna are fed to the support vector machine for training the classification system. It has been observed that presence of clay and trapping of water beneath the pavement resulted in subsidence of the patch. From the study, it can be deduced that the GPR can be used as a non-destructive tool for hazardous zone identification and pavement fault detection. Cite this article as: U. Joshi, R. Dev Garg, N. Sharma, V. Kumar Joshi and K. Sharma, “Hazardous zone identification by spectral analysis of ground penetrating radar response,” Electrica, 24(2), 503-514, 2024.
  • Real-Time IoT-Based Connected Vehicle Infrastructure for Intelligent Transportation Safety
    Neerav Sharma, Rahul D. Garg
    IEEE Transactions on Intelligent Transportation Systems, 2023
    The transportation sector faces severe consequences due to the incrementing population influx yielding congestions, fatalities and haphazard traffic scenarios. Advanced Driver Assistance Systems (ADAS) assists highly in such scenarios by eradicating probable accidents and ensures traffic safety. This paper presents intelligent transportation systems (ITS) approach through the connected vehicle technology infrastructure. YOLO v4 (You Only Look Once) inspired real-time computer vision capable of detecting vehicles, pedestrians and animals at high efficiency (0.9777 mean average precision) is deployed on the GPU (Graphics Processing Unit) which offered higher frame rate of detection (74.26 fps). The locations of animals and potholes were mapped through consistent survey and mobile app which relayed the detected locations to the cloud server forming a geospatial database. Clustered locations from the geospatial database on dense transportation network were utilized for constructing animal and pothole hotspot zones. A basic level of display warning was triggered when the vehicle approached animal and pothole areas. Furthermore, advanced alert comprising of display and sound alert was trigger when the vehicle approached hotspot zones. This was implemented using real-time Internet of things (IoT) and cloud infrastructure applications for continuous vehicle’s location monitoring and triggering as per the hotspot geo-locations. The proposed system ensured traffic safety and assisted in avoiding probable crashes and accidents that generally led to congestions and fatalities.
  • Cost reduction for advanced driver assistance systems through hardware downscaling and deep learning
    Neerav Sharma, Rahul Dev Garg
    Systems Engineering, 2022
    With the ever‐growing population density, transportation sector has become haphazard causing accidents and fatalities. It can be reduced by the effective utilization of intelligent transportation systems (ITS). The applications of advanced driver‐assistance systems (ADAS) and deep learning are trending globally with immense research potential and combined with ITS results into an intelligent system with decision‐taking capabilities. High‐priced driving modules are getting introduced day‐by‐day offering humongous processing power and computational capabilities. This research aims at utilizing the downscaled hardware for real‐time vehicular and pedestrian detection using a deep learning algorithm. YOLO v3 deep learning network is incorporated with NVIDIA series of GTX 1060 for real‐time object detection for assisting the ADAS systems. The system offers high precision (0.9618) of object detection in real time with high frame rate (74.36 fps). The comparative analysis between different GPU‐based hardware modules and the proposed module has been carried out keeping in mind the Indian context of automobile usages. The work lays a solid foundation for carrying out research for transportation analysis based on ADAS and deep learning for ITS such as real‐time congestion estimation and accident detection.
  • Real-Time Computer Vision for Transportation Safety using Deep Learning and IoT
    Neerav Sharma, Rahul Dev Garg
    8th International Conference on Engineering and Emerging Technologies Iceet 2022, 2022
    With the advancements in technology and application orientations, the field of computer vision is evolving at a rapid rate. Real-Time systems capable of detecting objects with high precision has been a spotlighted field of research. Autonomous traffic systems, self-driving cars and advanced driver assistance systems (ADAS) are the areas where computer vision plays an extensive role. This paper employs YOLO v4 deep learning based computer vision system for detecting vehicles, animals and pedestrians in real-time with high precision scores. The system is based on cross stage partial (CSPDarknet53) convolutional neural network serving as the backbone network for object detection. For precise detection of the entities, 16,300 image sequences were utilized for training the algorithm. For fast computation and detection, the algorithm was deployed on NVIDIA GTX 1060 GPU yielding into effective frames per second processing capabilities. The algorithm was trained for cars, bikes, pedestrians, cows and dogs yielding precision scores of 0.9912, 0.9868, 0.9783, 0.9770 and 0.9726 respectively. Also, the system alerts the vehicle in case of pothole areas nearby to ensure safety. Survey-based pothole and animal hotspots were collected and stored in the server geo-database. The vehicle approaching the hotspot triggers the alert system with acoustic feedback. The deployed real-time computer vision system serves as an effective system for real-time transportation entities detection applications laying a solid foundation for intelligent transportation systems, autonomous vehicles and advanced traffic applications.
  • Photo and thermoluminescence of Eu doped ZnO nanophosphors
    P. K. Upadhyay, Neerav Sharma, Shashank Sharma, Ravi Sharma
    Journal of Materials Science Materials in Electronics, 2021
  • Effective Utilization of A Low-Cost Solution for Remote Sensing of Vehicles and Pedestrians
    Neerav Sharma, Rahul Dev Garg
    2021 IEEE India Geoscience and Remote Sensing Symposium Ingarss 2021 Proceedings, 2021
    The field of remote sensing does not only confine to planetary and earth sciences but also in every field of science and technology. The hassled traffic patterns lead to fatalities and accidents and an efficient system comprising of detecting and analyzing the remotely sensed traffic components is of paramount essentiality. This study focuses at utilizing a downsized hardware along with deep learning algorithm for real-time detection of vehicles and pedestrians as per the Indian context of traffic and automotive markets. The system remotely senses the objects through computer vision and carries out the detection with high precision (0.98) and high frame rate (74 fps) necessary for intelligent transportation applications. The study provides a strong basis for utilization of a hardware system for assisting Advanced Driver Assistance Systems (ADAS) as per the Indian context of traffic and laying foundation for autonomous driving cars.
  • Dielectric and optical studies of CdSe nanoparticles: green synthesis
    Neearv Sharma, Shashank Sharma, Ravi Sharma
    Journal of Materials Science Materials in Electronics, 2020
  • POLESAT, an innovative e-health geomatic platform in decision-making based on: Geographical approach, medical knowledge visualization and geographic information system & web-mapping architecture
    A. Quesnel-Barbet, J. Soula, F. Dufossez, N. Sharma, A. Ruhela, R. Beuscart
    Irbm, 2013

RECENT SCHOLAR PUBLICATIONS

  • Satellite-driven assessment of urban pollution susceptibility in West Bengal, India
    N Sharma, S Bhattacharjee, RD Garg, K Sharma
    Journal of Environmental Engineering and Science, 1-11 , 2026
    2026
  • Reconfiguring Students' Role in the Age of Artificial Intelligence: A Multi-Level Sociological Analysis of Identity, Inequality, and Learning
    N Sharma, S Srivastava, HC Chandan
    Redefining the Roles of Educators and Students in the AI Era, 231-258 , 2026
    2026
  • Generative AI application for the elderly with dementia
    I Bhatt, N Sharma, R Kapuganti, D Parasar, S Kukreja
    Recent Advances in Computational Methods in Science and Technology, 451-456 , 2026
    2026
  • Can Indian Highways Support Zero-Emission Trucking?
    S Vaid, N Sharma, S Raghavan
    https://www.ceew.in/publications/how-can-india-boost-electric-charging … , 2025
    2025
  • Integrating Fuzzy Logic and Morphological Edge Detection for Enhanced UAV Orthomosaic Mapping
    P Singh, KN Nagesh, N Sharma
    2025 IEEE International Conference on Interdisciplinary Approaches in … , 2025
    2025
  • Predictive modeling of land cover changes in round-1 smart cities of India using cellular automata and GIS
    S Bhattacharjee, N Sharma, M Salim, RD Garg, K Sharma
    Discover Cities 2 (1), 6 , 2025
    2025
    Citations: 3
  • Spatial analysis and classification of land use patterns in Lucknow district, UP, India using GIS and random forest approach
    M Salim, S Bhattacharjee, N Sharma, K Sharma, RD Garg
    J. Geogr. Cartogr 8, 10230 , 2025
    2025
    Citations: 2
  • Sustainable management and agriculture resource technology system using remote sensing descriptors and IoT
    N Sharma, S Bhattacharjee, RD Garg, K Sharma, M Salim
    Geomatica 76 (2), 100040 , 2024
    2024
    Citations: 5
  • Hybrid Quantum Classical Convolutional Neural Network with Spider Wasp Optimizer for Enhanced Data Security in Cloud Environments
    M Sharma, M Sharma, N Sharma
    2024 4th International Conference on Sustainable Expert Systems (ICSES), 421-427 , 2024
    2024
  • Enhanced Real-Time Computer Vision and Intelligent Decision-Making for Autonomous Vehicle Applications
    N Sharma, RD Garg, S Bhattacharjee, PP Dash
    2024
  • Hazardous zone identification by spectral analysis of ground penetrating radar response
    U Joshi, RD Garg, N Sharma, VK Joshi, K Sharma
    Electrica 24 (2), 503-514 , 2024
    2024
    Citations: 2
  • Modeling the Future Simulation of Friction Stir Processing in Hybrid Composite Materials
    M Sharma, M Sharma, N Sharma
    Utilizing Friction Stir Techniques for Composite Hybridization, 437-458 , 2024
    2024
  • Building sustainable smart cities through cloud and intelligent parking system
    M Sharma, M Sharma, N Sharma, S Boopathi
    Handbook of Research on AI and ML for Intelligent Machines and Systems, 195-222 , 2024
    2024
    Citations: 49
  • Building Sustainable Smart Cities: Integrating Cloud Technology and Intelligent Parking Systems
    M Sharma, M Sharma, N Sharma
    The Convergence of Self-Sustaining Systems With AI and IoT, 104-129 , 2024
    2024
    Citations: 1
  • A cutting-edge ai-and-iot-powered cyber secured intrusion detection system
    M Sharma, M Sharma, N Sharma
    2023 International Conference on Innovative Computing, Intelligent … , 2023
    2023
    Citations: 1
  • Real-time IoT-based connected vehicle infrastructure for intelligent transportation safety
    N Sharma, RD Garg
    IEEE transactions on intelligent transportation systems 24 (8), 8339-8347 , 2023
    2023
    Citations: 43
  • Advanced transportation safety using real-time GIS-based alarming system for animal-prone zones and pothole areas
    N Sharma, RD Garg
    Journal of transportation engineering, Part A: Systems 149 (4), 04023003 , 2023
    2023
    Citations: 7
  • Real-time computer vision for transportation safety using deep learning and iot
    N Sharma, RD Garg
    2022 International Conference on Engineering and Emerging Technologies … , 2022
    2022
    Citations: 7
  • Cost reduction for advanced driver assistance systems through hardware downscaling and deep learning
    N Sharma, RD Garg
    Systems Engineering 25 (2), 133-143 , 2022
    2022
    Citations: 18
  • POS-811 A RETROSPECTIVE STUDY TO ASSESS DROPOUT RATE AND ITS CAUSES IN LIVING DONOR TRANSPLANT PROGRAM IN INDIA
    A Sharma, K Sharma, N Sharma, V Kumar, HS Kohli
    Kidney International Reports 7 (2), S348 , 2022
    2022
    Citations: 1

MOST CITED SCHOLAR PUBLICATIONS

  • Building sustainable smart cities through cloud and intelligent parking system
    M Sharma, M Sharma, N Sharma, S Boopathi
    Handbook of Research on AI and ML for Intelligent Machines and Systems, 195-222 , 2024
    2024.0
    Citations: 49
  • Real-time IoT-based connected vehicle infrastructure for intelligent transportation safety
    N Sharma, RD Garg
    IEEE transactions on intelligent transportation systems 24 (8), 8339-8347 , 2023
    2023.0
    Citations: 43
  • Profile of cardiac tamponade in the medical emergency ward of a North Indian hospital.
    S Jain, N Sharma, S Varma, A Rajwanshi, JS Verma, BK Sharma
    The Canadian journal of cardiology 15 (6), 671-675 , 1999
    1999.0
    Citations: 35
  • Influence of product thickness, chamber pressure and heating conditions on production rate of freeze-dried yoghurt
    NK Sharma, CP Arora
    International journal of refrigeration 18 (5), 297-307 , 1995
    1995.0
    Citations: 35
  • GCD Based Blind Super-Resolution for Remote Sensing Applications
    N Sharma, PP Dash, P Saxena
    2nd International Conference on Energy, Power and Environment: Towards Smart … , 2018
    2018.0
    Citations: 23
  • Cost reduction for advanced driver assistance systems through hardware downscaling and deep learning
    N Sharma, RD Garg
    Systems Engineering 25 (2), 133-143 , 2022
    2022.0
    Citations: 18
  • INFLUENCE of CONCENTRATION of MILK SOLIDS ON FREEZE‐DRYING RATE of YOGHURT and ITS QUALITY 1
    NK Sharma, CP Arora, BK Mital
    Journal of food process engineering 15 (3), 187-198 , 1992
    1992.0
    Citations: 16
  • Prediction of transient temperature distribution during freeze drying of yoghurt
    NK Sharma, CP Arora
    Drying Technology 11 (7), 1863-1883 , 1993
    1993.0
    Citations: 15
  • Photo and thermoluminescence of Eu doped ZnO nanophosphors
    PK Upadhyay, N Sharma, S Sharma, R Sharma
    Journal of Materials Science: Materials in Electronics 32 (13), 17080-17093 , 2021
    2021.0
    Citations: 14
  • Dielectric and optical studies of CdSe nanoparticles: green synthesis
    N Sharma, R Sharma, Shashank & Sharma
    Journal of Materials Science: Materials in Electronics , 2020
    2020.0
    Citations: 11
  • Transient waves due to mechanical loads in elasto-thermo-diffusive solids
    JN Sharma, NK Sharma, KK Sharma
    Advances in Applied Mathematics and Mechanics 3 (1), 87-108 , 2011
    2011.0
    Citations: 11
  • Contribution of female labour in agriculture: A case study of Ranchi District (Bihar)
    LN Dutta, N Sharma
    Indian Journal of Agricultural Economics 40 (3), 273 , 1985
    1985.0
    Citations: 9
  • Advanced transportation safety using real-time GIS-based alarming system for animal-prone zones and pothole areas
    N Sharma, RD Garg
    Journal of transportation engineering, Part A: Systems 149 (4), 04023003 , 2023
    2023.0
    Citations: 7
  • Real-time computer vision for transportation safety using deep learning and iot
    N Sharma, RD Garg
    2022 International Conference on Engineering and Emerging Technologies … , 2022
    2022.0
    Citations: 7
  • Sustainable management and agriculture resource technology system using remote sensing descriptors and IoT
    N Sharma, S Bhattacharjee, RD Garg, K Sharma, M Salim
    Geomatica 76 (2), 100040 , 2024
    2024.0
    Citations: 5
  • Hypothyroidism--an unusual cause of cardiac tamponade.
    N Sharma, S Jain, S Kumari, S Varma
    Australian and New Zealand journal of medicine 30 (6), 731-731 , 2000
    2000.0
    Citations: 5
  • kulshreshtha S, Parakh R, Bansal A, Sinha RR (2013) Screening of prescriptions in geriatric population in a tertiary care teaching hospital in north India
    N Sharma, U Advani
    The Journal of Phytopharmacology 2 (5), 38-45 , 0
    Citations: 5
  • Molecular diagnosis of Mycobacterium bovis as the cause of tuberculosis in a camel
    R Verma, DS Sena, N Sharma, K Alex, RS Pamane, KML Pathak
    Indian Journal of Animal Sciences (India) 81 (11) , 2011
    2011.0
    Citations: 4
  • Predictive modeling of land cover changes in round-1 smart cities of India using cellular automata and GIS
    S Bhattacharjee, N Sharma, M Salim, RD Garg, K Sharma
    Discover Cities 2 (1), 6 , 2025
    2025.0
    Citations: 3
  • Effective utilization of a low-cost solution for remote sensing of vehicles and pedestrians
    N Sharma, RD Garg
    2021 IEEE International India Geoscience and Remote Sensing Symposium … , 2021
    2021.0
    Citations: 3

Publications

Sharma. K., and Sharma. N., (2020) “Environmental Management Through the Assessment of Impact of Urban Growth Through Remote Sensing Techniques”, Journal of Applied Sciences, Science Alert. DOI: 10.3923/

RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)

• Sharma, N., & Garg, R.D. (2023). Real-Time IoT-based Connected Vehicle Infrastructure for Intelligent Transportation Safety. IEEE Transactions on Intelligent Transportation Systems, 24 (8), 8339-8347. {Q1, I.F. = 9.5}
• Sharma, N., & Garg, R.D. (2023). Advanced Transportation Safety using Real-Time GIS-based Alarming System for Animal Prone Zones and Pothole Areas. Journal of Transportation Engineering, Part A: Systems, American Society of Civil Engineering (ASCE), 149 (4), 1-12. {Q2, I.F. = 2.3}
• Sharma, N., & Garg, R.D. (2023). Real-Time Computer Vision for Transportation Safety using Deep Learning and IoT. Proceedings of the 8th IEEE International Conference on Engineering and Emerging Technologies (ICEET), pp 1-5. (Best Paper Award).
• Sharma, N., & Garg, R.D. (2022). Cost reduction for advanced driver assistance systems through hardware downscaling and deep learning. Systems Engineering, Wiley, 25 (2), 133-143. {Q2, I.F. = 2.3}
• Sharma, N., & Garg, R.D. (2022). Effective Utilization of A Low-Cost Solution for Remote Sensing of Vehicles and Pedestrians. 2021 IEEE International India Geoscience and Remote Sensing Symposium (InGARSS), pp 312-315.
• Sharma, N., & Garg, R.D. (2022). Connected Vehicle Technology and its Extensibility to Intelligent Transportation