Deep learning-based smart air quality management and prediction system integrating satellite imagery, ground-based internet-of-things sensors, and natural language processing technologies for forecasting pollution
	BANSAL S; GUPTA S; RATHER M A; KUMAR M; TIPU R K
	2025-03-31
专利权人	BANSAL S (BANS-Individual) ; GUPTA S (GUPT-Individual) ; RATHER M A (RATH-Individual) ; KUMAR M (KUMA-Individual) ; TIPU R K (TIPU-Individual)
申请日期	2025-03-31
专利号	IN202511032159-A
成果简介	NOVELTY - The system has satellite imagery, ground-based internet-of-things (IoT) sensors, and natural language processing (NLP) technologies for forecasting pollution and recommending real-time mitigation actions. A cloud-based backend infrastructure provides secure scalable data storage, and computational resources for ongoing data analysis, model training, and prediction accuracy improvement. An integrated NLP-powered policy recommendation module analyzes regulatory frameworks and pollution data to provide automated mitigation strategies. An interactive graphical user interface (GUI) visualizes predictive air quality analytics, actionable policy recommendations, and real time alerts through intuitive geographic information system (GIS)-based heatmaps and dashboards. USE - Deep learning-based smart air quality management and prediction system for monitoring, predicting, and managing air pollution across urban, industrial, and residential environments. ADVANTAGE - The system provides advanced forecasting capabilities instead of only real-time monitoring, enabling proactive environmental management. The system generates dynamic regulation-based policy recommendations using NLP rather than relying on static rule-based actions, and supports multi pollutant and multi-source data integration (satellite + ground sensors), thus improving prediction accuracy. The system enhances decision-making through geospatial visualization and personalized dashboards for stakeholders, and improves adaptability and scalability for deployment in smart cities, industrial zones, and government agencies. DETAILED DESCRIPTION - An INDEPENDENT CLAIM is also included for a method for accurately predicting air pollution levels using combined time-series and spatial data sources.
IPC 分类号	G06N-020/00 ; G06N-003/044 ; G06N-003/08 ; G06Q-050/26 ; G06V-010/764
国家	印度
专业领域	信息技术
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/13306
专题	中国科学院新疆生态与地理研究所
作者单位	1.BANSAL S (BANS-Individual) 2.GUPTA S (GUPT-Individual) 3.RATHER M A (RATH-Individual) 4.KUMAR M (KUMA-Individual) 5.TIPU R K (TIPU-Individual)
推荐引用方式 GB/T 7714	BANSAL S,GUPTA S,RATHER M A,et al. Deep learning-based smart air quality management and prediction system integrating satellite imagery, ground-based internet-of-things sensors, and natural language processing technologies for forecasting pollution. IN202511032159-A[P]. 2025.

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