TU1.P3.2
A MULTIMODAL FRAMEWORK FOR SPATIOTEMPORAL CAUSAL ANALYSIS OF MUMBAI’S AIR POLLUTION USING SOCIAL MEDIA INSIGHTS AND REMOTE SENSING
Kaushal Patil, University of Southern California, United States; Chaitanya Kakade, Thadomal Shahani Engineering College, India; Ujwala Bharambe, University of Mumbai, India; Chetan Mahajan, Indian Institute of Technology Bombay, India
Session:
TU1.P3: IoT in Geoscience and Remote Sensing Oral
Track:
AI and Big Data
Location:
Plaza: Room P3
Presentation Time:
Tuesday, 5 August, 08:15 - 08:30
Session Co-Chairs:
Hind Oubanas, INRAE and Momin Uppal, Lahore University of Management Sciences
Presentation
Discussion
Resources
No resources available.
Session TU1.P3
TU1.P3.1: Robust TDOA Localization under Sparse NLOS via Geman-McClure with Balance Parameter
Qinyu Ding, Longwen Wu, Yaqin Zhao, Yang Cao, Harbin Institute of Technology, China; Kunyu Han, Civil Aviation University of China, China; Zhilu Wu, Harbin Institute of Technology, China
TU1.P3.2: A MULTIMODAL FRAMEWORK FOR SPATIOTEMPORAL CAUSAL ANALYSIS OF MUMBAI’S AIR POLLUTION USING SOCIAL MEDIA INSIGHTS AND REMOTE SENSING
Kaushal Patil, University of Southern California, United States; Chaitanya Kakade, Thadomal Shahani Engineering College, India; Ujwala Bharambe, University of Mumbai, India; Chetan Mahajan, Indian Institute of Technology Bombay, India
TU1.P3.3: A MULTI-LAYERED TOKENIZATION FRAMEWORK FOR IOT AND SATELLITE DATA INTEGRATION TO ENHANCE ENVIRONMENTAL MONITORING AND DISASTER MITIGATION
Amir Semnani, Guowu Yang, University of Electronic Science and Technology of China, China
TU1.P3.5: Spatiotemporal Air Quality Mapping in Urban Areas Using Sparse Sensor Data, Satellite Imagery, Meteorological Factors, and Spatial Features
Osama Ahmad, Zubair Khalid, Muhammad Tahir, Momin Uppal, Lahore University of Management Sciences, Pakistan
Resources
No resources available.