Science of Sensor System Software

传感器系统软件科学

基本信息

批准号：
EP/N007565/1
负责人：
Muffy Calder
金额：
$ 533.09万
依托单位：
University of Glasgow
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2016
资助国家：
英国
起止时间：
2016 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FN007565%2F1
关键词：
Science Sensor System Software

项目摘要

Sensors are everywhere, facilitating real-time decision making and actuation, and informing policy choices. But extracting information from sensor data is far from straightforward: sensors are noisy, prone to decalibrate, and may be misplaced, moved, compromised, and generally degraded over time. We understand very little about the issues of programming in the face of pervasive uncertainty, yet sensor-driven systems essentially present the designer with uncertainty that cannot be engineered away. Moreover uncertainty is a multi-level phenomenon in which errors in deployment can propagate through to incorrectly-positioned readings and then to poor decisions; system layering breaks down when exposed touncertainty. How can we be assured a sensor system does what we intend, in a range of dynamic environments, and how can we make a system ``smarter'' ? Currently we cannot answer these questions because we are missing a science of sensor system software. We will develop the missing science that will allow us to engineer for the uncertainty inherent in real-world systems. We will deliver new principles and techniques for the development and deployment of verifiable, reliable, autonomous sensor systems that operate in uncertain, multiple and multi-scale environments. The science will be driven and validated by end-user and experimental applications.

传感器无处不在，促进实时决策和执行，并为政策选择提供信息。但从传感器数据中提取信息远非直截了当：传感器噪音大、容易校准，并且可能会被放错位置、移动、受损，并且通常会随着时间的推移而退化。面对普遍的不确定性，我们对编程问题知之甚少，但传感器驱动的系统本质上给设计者带来了无法通过工程消除的不确定性。此外，不确定性是一种多层次的现象，部署错误可能会传播到错误定位的读数，然后导致错误的决策；当暴露于不确定性时，系统分层就会崩溃。我们如何确保传感器系统在一系列动态环境中按照我们的预期行事，以及如何使系统“更智能”？目前我们无法回答这些问题，因为我们缺少传感器系统软件科学。我们将开发缺失的科学，使我们能够针对现实世界系统固有的不确定性进行设计。我们将提供新的原理和技术，用于开发和部署在不确定、多重和多尺度环境中运行的可验证、可靠、自主的传感器系统。该科学将由最终用户和实验应用程序驱动和验证。