HazPrep 工人培训 - 社区风险概况-猫眼课题宝

HazPrep 工人培训 - 社区风险概况

批准号：

9339963

负责人：

Henry Ryng

金额：

$10.0万

依托单位：

INXSOL, LLC

依托单位国家：

美国

项目类别：

财政年份：

2017

资助国家：

美国

项目状态：

已结题

起止时间：

2017-06-01 至 2018-06-30

来源：

https://reporter.nih.gov/project-details/9339963

关键词：

Address Algorithms Awareness Big Data Businesses Centers for Disease Control and Prevention (U.S.)Collaborations Commerce Communities Community Practice Community of Practice Computers Containment Data Development Disasters E-learning Earthquakes Emergency response Environmental Hazards Environmental Health Excision Feedback Feeds Floods Focus Groups Formulation Fostering Future Generations Hazardous Substances Health Hurricane Imagery Individual Information Sciences Knowledge Legal patent Location Maps Modeling Names National Institute of Environmental Health Sciences Occupational Health Ontology Outcome Phase Preparation Research Personnel Resources Risk Role Safety Site Source Stream Structure Suggestion System Technology Testing Time Training Training Activity Training Programs Transportation Universities Work base certificate program cloud based commercialization design emergency service responder experience feeding hazard improved indexing innovation interest learning strategy peer programs prototype research and development resilience response simulation social social media usability wasting

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PROJECT SUMMARY/ABSTRACT A worker's personal hazard profile (PHP) is a function of hazards present and his/her exposure level to those hazards. Workers with an elevated level of risk are those who can be engaged in activities related to or working around hazardous materials, waste generation, removal, containment, transportation, and emergency response. inXsol believes two components are necessary to implement a sophisticated geo-personalized, role-based, all-hazards-training activity platform: PHP and cloud based automated community profile algorithms. Our approach solves a problem for communities (knowledge about local risks) and a problem for worker safety (hazards workers or responders can prepare for). The proposal includes innovative use of big data algorithms for community profiles and fusion with PHP allowing for targeted and personalized training into a platform we have named HazPrep.

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