Designing Multi-sensory Personal Aids in the IoT Age

该计划的目标是物联网(IoT)的质量驱动设计，重点是构建在多传感无线系统上的健康/健康应用。将探索安全系统的设计和验证，包括在网络边缘加入可靠、廉价和可用的机器智能(MI)。从长远来看，我们的进步应该能够实现个性化药物系统，其中主要的生理状态变量被跟踪，以个性化药物、运动和营养剂量，导致精确控制，减少广泛的不良反应，特别是对慢性病。短期目标包括以质量为导向的可靠系统设计、健康试验床的开发和信任/认证合规。针对慢性健康状况(糖尿病、呼吸)和衰老的系统将被调整，以改善或取消(单独进行的)人体试验。MI越来越多的使用带来了可靠性和可解释(信任)方面的问题，因此它们可以安全地添加到健康和健康设备中。加速器将设计用于分布式、保护隐私的人类活动识别(HAR)和其他MI，以及利用嵌入网络边缘的设备精心设计的新功能。为了实现不同的质量目标，我们将结合我们的属性监视器和特定于领域的工具。确保不同利益相关者正确处理数据目前代价高昂，因为普通物联网平台成为安全目标，这尤其危及健康和健康应用程序的隐私，为此我们将在安全设计、信任和安全方面进行几个方面的研究。除了基于断言的质量保证、监控和验证技术外，我们还将探索在医疗保健和健康中使用的物联网设备网络中可行的信任机制的无否认区块链，特别是身体传感器网络(BSN)。将开发可扩展的区块链技术，以实现电子健康记录，解决在医生、药房、医疗保险公司和患者之间的交换中提供可信处方、药物和传感器数据的挑战，从而实现健康/健康养生方案，并最终实现精确(个性化)药物。因此，关注医疗保健物联网的可用性和持续服务质量改进的研究将与安全和隐私问题结合起来。我们将探索使用新的混合系统优化和验证方法，以及新兴计算领域，如不精确计算、内存计算、可逆计算或量子计算。这项研究的未来保障将包括抗量子计算的安全性和可扩展的可逆电路合成，其好处包括从能效到智能、安全和隐私保护。我们将培养20-30名行业和学术需求较高的HQP。

This program targets quality-driven design of Internet of Things (IoT), with emphasis on health/wellness applications built on multi-sensory wireless systems. Design and validation will be explored for secure and safe systems including dependable, inexpensive and usable Machine Intelligence (MI) incorporation on the network edge. In long-term, our advances should enable the personalized medicine systems, where major physiological state variables are tracked to personalize medicaments, exercise and nutrition dosing, leading to precise control that reduces widespread adverse effects, especially for chronic conditions. Short-term goals include the quality-driven design of dependable systems, the development of health testbeds and the trust/certification compliance. Systems for chronic health conditions (diabetes, respiration) and aging will be tuned to improve or obviate the (separately undertaken) human trials. The increasing use of MI creates problems with dependability and with being explainable (trusted), such that they can be safely added to health and wellness devices. Accelerators will be designed for distributed, privacy- preserving human activity recognition (HAR) and other MI, as well as harnessing the carefully designed new capabilities of the devices embedded in the edge of the network. To achieve diverse quality goals, we will combine our property monitors with domain-specific tools. Ensuring proper data handling by diverse stakeholders is currently costly, as common IoT platforms become security targets, which especially endangers privacy in health and wellness applications, towards which we will undertake several threads of research in secure design, trust and safety. Besides the assertion-based quality assurance, monitoring and verification techniques, we will explore the repudiation-free blockchain for feasible trust mechanisms in networks of IoT devices used in healthcare and wellness, including notably Body Sensor Networks (BSNs). Scalable blockchain technologies will be developed for the realization of electronic health records addressing the challenges of providing trusted prescriptions, medicaments and sensor data in the exchange between medical practitioners, pharmacies, insurance companies and patients, allowing the health/wellness regimen and, ultimately, precision (personalized) medicine. Research focus on the usability and continuous service quality improvements of IoT for healthcare will be hence combined with the security and privacy concerns. We will explore the use of new hybrid system optimization and verification methods, as well as the emerging computing fields, such as the imprecise, in-memory, reversible or quantum computing. Future-proofing of the research will include the quantum computing-resistant security and scalable reversible circuit synthesis, with benefits ranging from energy-efficiency to intelligence, safety and privacy preservation. We will train 20-30 HQPs in high demand for industry and academy.