Vital signs monitoring classification system for use in e.g. forest, has machine learning models for classifying environmental conditions into risk levels, and predictive algorithms analyze historical and real-time data to forecast disaster scenarios
	BUSHRA M; SAI P A; REDDY S T; DURGA V B C; VSRK P G; PRASAD D D
	2025-03-27
专利权人	POTTI SRIRAMULU CHALAVADI MALLIKARJUNA (POTT-Non-standard)
申请日期	2025-03-27
专利号	IN202541028888-A
成果简介	NOVELTY - The system has a dashboard providing real-time monitoring, risk classification, and automated alerts for stakeholders, where monitoring and classification outputs are integrated with disaster response frameworks to enhance inter-agency coordination and resource optimization. An architecture is scalable to monitor diverse ecosystems e.g. forests. A machine learning model classifies environmental conditions e.g. normal, into risk levels. Predictive algorithms analyze historical and real time data to forecast disaster scenarios such as wildfires. Air quality sensors measure pollutants e.g. carbon dioxide (CO2). Water quality sensors monitor pH levels, dissolved oxygen, and contamination levels. USE - Classification system for monitoring an environmental vital sign e.g. air pollutants such as CO2, nitrogen dioxide (NO2), and particulate matter (PM) 2.5, water pH levels and temperature anomalies, and for disaster management and environmental risk assessment to safeguard ecosystems. Uses include but are not limited to forests, rivers and coastal areas and urban areas. ADVANTAGE - The system enhances disaster management and environmental risk assessment by leveraging real-time data and machine learning algorithms. The system monitors the key environmental indicators, classifies risks, and predicts disaster scenarios, so as to enable proactive measures to safeguard ecosystems and mitigate environmental damage. The system ensures leveraging machine learning (ML) and sensor networks so as to identify patterns, classify risks and predicts disaster scenarios, thus empowering stakeholders such as governments, NGOs, and environmental agencies, to implement timely interventions and optimize resource allocation, and hence protecting ecosystems and reducing disaster impacts. The system integrates with existing disaster response systems, thus enhancing coordination between agencies and optimizing response strategies.
IPC 分类号	G06Q-010/0635 ; G06Q-010/067 ; G06Q-050/26 ; G06V-020/10 ; G16H-050/30
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/13484
专题	中国科学院新疆生态与地理研究所
作者单位	POTTI SRIRAMULU CHALAVADI MALLIKARJUNA (POTT-Non-standard)
推荐引用方式 GB/T 7714	BUSHRA M,SAI P A,REDDY S T,et al. Vital signs monitoring classification system for use in e.g. forest, has machine learning models for classifying environmental conditions into risk levels, and predictive algorithms analyze historical and real-time data to forecast disaster scenarios. IN202541028888-A[P]. 2025.

条目包含的文件
条目无相关文件。

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。