A5064244258- Air Quality Monitoring and Forecasting
- Impact of Light on Environment and Health
- Air Quality and Health Impacts
- Indoor and Outdoor Localization Technologies
- UAV Applications and Optimization
- Traffic Prediction and Management Techniques
- Autonomous Vehicle Technology and Safety
- Human Mobility and Location-Based Analysis
- Advanced Optical Sensing Technologies
- Vehicular Ad Hoc Networks (VANETs)
- Evacuation and Crowd Dynamics
- Millimeter-Wave Propagation and Modeling
- Distributed Control Multi-Agent Systems
- Human-Automation Interaction and Safety
- Video Surveillance and Tracking Methods
- Reinforcement Learning in Robotics
- Mobile Crowdsensing and Crowdsourcing
- Advanced Wireless Communication Technologies
- COVID-19 impact on air quality
- Advanced MIMO Systems Optimization
- Gaze Tracking and Assistive Technology
- Bluetooth and Wireless Communication Technologies
- Noise Effects and Management
- Transportation Planning and Optimization
Indian Institute of Technology Kharagpur
2022-2025
National Institute of Technology Durgapur
2020
Unmanned Aerial Vehicles (UAVs) can be utilized as aerial base stations to establish wireless communication networks in various challenging scenarios, such emergency disaster areas and rural areas. Under large regions, the would require UAVs form (backhaul) links among each other provide end-to-end services between two or more ground users (via one UAVs). Such UAV backhauling may severely compromised if are knocked off during time of operation – it due hardware/software faults, limited...
Indoor air pollution is a major issue in developing countries such as India and Bangladesh, exacerbated by factors traditional cooking methods, insufficient ventilation, cramped living conditions, all of which elevate the risk health issues lung infections cardiovascular diseases. With World Health Organization associating around 3.2 million annual deaths globally to household pollution, gravity problem clear. Yet, extensive empirical studies exploring these unique patterns indoor...
Intelligent city transportation systems are one of the core infrastructures a smart city. The true ingenuity such an infrastructure lies in providing commuters with real-time information about citywide transport like public buses, allowing them to pre-plan their travel. However, prior for buses is inherently challenging because diverse nature different stay-locations where bus stops. Although straightforward factors stay duration extracted from unimodal sources GPS at these locations look...
Efficient air quality sensing serves as one of the essential services provided in any recent smart city. Mostly facilitated by sparsely deployed Air Quality Monitoring Stations (AQMSs) that are difficult to install and maintain, overall spatial variation heavily impacts monitoring for locations far enough from these pre-deployed public infrastructures. To mitigate this, we this article propose a framework named AQuaMoHo can annotate data obtained low-cost thermo-hygrometer (as sole physical...
Continuous monitoring of driver attentiveness inside a car has been significant importance for quite some time. However, the state-of-the-art techniques are primarily inclined toward image-based data, which is invasive and, therefore, could pose challenges in pervasive adoption such system. This work proposes novel approach continuous monitoring, leveraging millimeter Wave (mmWave) sensing to address that. The infrastructure compact, lightweight, and bears exclusive potential be adopted...
Detecting dangerous driving has been of critical interest for the past few years. However, a practical yet minimally intrusive solution remains challenging as existing technologies heavily rely on visual features or physical proximity. With this motivation, we explore feasibility purely using mm Wave radars to detect behaviors. We first study characteristics and find some unique patterns range-doppler caused by 9 typical actions. then develop novel Fused-CNN model instances from regular...
Smart cities are generally equipped with Air Quality Monitoring Stations (AQMS) as public infrastructure to have an overall perception of the air quality. However, spatial density samples from available AQMS is low, a high cost deployment and maintenance. Due variation quality sparse AQMSs within city, it impossible reliably obtain location far deployed AQMS. This paper provides framework called AQuaMoHo that augments this existing system low-cost alternative can even help residents city...
Unmanned aerial vehicles (UAVs) are widely used for missions in dynamic environments. Deep Reinforcement Learning (DRL) can find effective strategies multiple agents that need to cooperate complete the task. In this article, challenge of controlling movement a fleet UAVs is addressed by Multi-Agent (MARL). The collaborative UAV be controlled centrally and also decentralized fashion, which studied work. We consider military environment with UAVs, whose task destroy enemy targets while...
Changing public perceptions and government regulations have led to the widespread use of low-cost air quality monitors in modern indoor spaces. Typically, these detect pollutants augment end user's understanding her environment. Studies shown that having access one's context reinforces urge take necessary actions improve over time. Thus, activities significantly influence quality. Such correlation can be exploited get hold sensitive from side-channel fluctuations. This study explores odds...
Indoor air pollution is a major issue in developing countries such as India and Bangladesh, exacerbated by factors like traditional cooking methods, insufficient ventilation, cramped living conditions, all of which elevate the risk health issues lung infections cardiovascular diseases. With World Health Organization associating around 3.2 million annual deaths globally to household pollution, gravity problem clear. Yet, extensive empirical studies exploring these unique patterns indoor...
Public city bus services across various developing cities inhabit multiple stay-locations on the routes due to ad-hoc stops provide on-demand passenger boarding and alighting services. Characterizing these is essential correctly develop models for transit patterns used in digital navigation In this poster, we create a deep learning-driven methodology characterize over based crowd-sensing contextual information. Experiments 720km of travel data semi-urban India indicate promising results from...
Intelligent city transportation systems are one of the core infrastructures a smart city. The true ingenuity such an infrastructure lies in providing commuters with real-time information about citywide transports like public buses, allowing her to pre-plan travel. However, prior for buses is inherently challenging because diverse nature different stay-locations that bus stops. Although straightforward factors stay duration, extracted from unimodal sources GPS, at these locations look...
Detecting dangerous driving has been of critical interest for the past few years. However, a practical yet minimally intrusive solution remains challenging as existing technologies heavily rely on visual features or physical proximity. With this motivation, we explore feasibility purely using mmWave radars to detect behaviors. We first study characteristics and find some unique patterns range-doppler caused by 9 typical actions. then develop novel Fused-CNN model instances from regular...