Designing Multi-sensory Personal Aids in the IoT Age

设计物联网时代的多感官个人辅助设备

• 批准号: RGPIN-2019-05474
• 负责人: Zilic, Zeljko
• 金额: $ 2.4万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=752329
• 关键词: Designing; Multi; sensory; Personal; Aids

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.

该程序针对物联网质量驱动的设计（IoT），重点是建立在多感官无线系统上的健康/健康应用程序。将探索设计和验证的安全系统，包括在网络边缘纳入的可靠，便宜和可用的机器智能（MI）。从长远来看，我们的进步应该使个性化的医学系统能够跟踪主要的物理状态变量以个性化药物，运动和营养剂量，从而确切控制，从而减少宽度不良的不良影响，尤其是对于慢性病。短期目标包括依赖系统的质量驱动设计，健康测试床的开发以及信任/认证合规性。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消除（分别进行）人类试验。 MI的越来越多会产生可靠性和被解释（可信赖）的问题，以便可以将它们安全地添加到健康和保健设备中。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，并利用嵌入在网络边缘的设备的精心设计的新功能。为了实现多样性质量目标，我们将将我们的物业监视器与特定领域的工具相结合。目前，确保潜水员利益相关者的适当数据处理是昂贵的，因为普通的物联网平台成为安全目标，尤其是危害健康和保健应用中的隐私，我们将在此方面对安全设计，信任和安全性进行多项研究。除了基于断言的质量保证，监测和验证技术外，我们还将探索无抵消的区块链，以实现医疗保健和健康的物联网设备网络中可行的信任机制，包括人体传感器网络（BSNS）。将开发可扩展的区块链技术，以实现电子健康记录，以解决在医生，药房，保险公司和患者之间交换中提供可信赖的处方，药物和传感器数据的挑战，从而允许健康/健康方案，并最终，最终，精确（个性化）药物。因此，研究重点是物联网对医疗保健的可用性和持续服务质量改进，将是结合安全性和隐私问题。我们将探讨新的混合系统优化和验证方法的使用，以及新兴的计算字段，例如启动，内存，可逆或量子计算。该研究的未来范围将包括抗量子计算的安全性和可扩展的可逆电路合成，从能源效率到智能，安全性和隐私保护的好处。我们将培训20-30台HQP对行业和学院的需求高。