SBIR Phase I: Prediction of impending earthquakes using data from geographically distributed array of sensors for monitoring behavior of companion animals and large scale data anal

SBIR 第一阶段：使用来自地理分布的传感器阵列的数据来预测即将发生的地震，用于监测伴侣动物的行为和大规模数据分析

• 批准号: 1416601
• 负责人: Alex Treiner
• 金额: $ 15万
• 依托单位: PET WIRELESS, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1416601&HistoricalAwards=false
• 关键词: SBIR; Phase; Prediction; impending; earthquakes

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is that it may potentially save lives and avoid hardship for millions of people around the world by predicting impending earthquakes significantly in advance of their occurrence. Dozens of destructive earthquakes occur every year. Reliable and timely prediction of earthquake occurrence has been a holy grail of seismic research for many years, since it would offer the possibility of minimizing casualties and economic loss. This project proposes to improve the accuracy of earthquake prediction by unobtrusively monitoring changes in the behavior of companion animals (such as cats and dogs) and combining this information with data from seismic sensors and other sources. Successful completion of the project will allow the development of powerful data analytics for earthquake prediction.This Small Business Innovation Research (SBIR) Phase I project is addressing a very challenging problem of advanced earthquake prediction that has not been solved to date, despite significant advances in science and technology over the past half century and massive international efforts of governmental, academic and other institutions. The objective of this project is to collect animal behavior data using proprietary sensors, and develop analytics for animal behavior data processed in conjunction with data from seismic, GPS and other sensors, with the goal of establishing correlations between changes in animal behavior prior to impending earthquakes and the time of occurrence, location, and magnitude of the earthquakes. Numerous attempts to prove such correlation have been inconclusive to date. This project, however, takes a different approach by using proprietary sensors to collect objective scientific data from companion animals by means of sensors that are unobtrusive and do not affect the animals' behavior. This project aims to demonstrate data relevance on a small scale, using data collected from a small number of animals over a relatively short period of time in a well-studied and continuously monitored seismically active area with high probability of frequent earthquake occurrence.

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力是，它可能通过在地震发生之前预测即将发生的地震，从而挽救生命，避免世界各地数百万人的苦难。每年都会发生数十次破坏性地震。可靠、及时地预测地震的发生是多年来地震研究的圣杯，因为它将提供最小化人员伤亡和经济损失的可能性。该项目提出通过不引人注目地监测伴侣动物（如猫和狗）的行为变化，并将这些信息与地震传感器和其他来源的数据相结合，提高地震预测的准确性。这个小型企业创新研究（SBIR）第一期项目旨在解决一个极具挑战性的高级地震预测问题，尽管在过去的半个世纪里科学技术取得了巨大的进步，国际上政府、学术界和其他机构也做出了巨大的努力，但迄今为止，这个问题还没有得到解决。该项目的目标是使用专有传感器收集动物行为数据，并结合地震，GPS和其他传感器的数据处理动物行为数据，以建立动物行为变化与地震发生时间，地点和震级之间的相关性。迄今为止，证明这种相关性的许多尝试都没有结果。然而，该项目采取了不同的方法，通过使用专有传感器收集伴侣动物的客观科学数据，这些传感器不引人注目，不会影响动物的行为。该项目的目的是在小规模上证明数据的相关性，使用在一个经过充分研究和持续监测的地震活跃地区（地震频繁发生的可能性很高）在相对较短的时间内从少量动物收集的数据。