Using big data analytics to improve decision making of system-on-module based solutions

可穿戴设备正变得越来越受欢迎，预计到2019年将达到2.45亿台，价值250亿美元。为了使可穿戴设备在各种应用中能够快速发展，已经提出了模块上系统(SOM)解决方案。随着SOM解决方案变得更加强大和突出，它们正在发挥更智能的作用，并被用于各种应用，如运动训练和康复/治疗。因此，SOM利益相关者需要分析来改进基于其解决方案的决策。为了推进最先进的SOM技术并保持加拿大SOM技术制造商的领先地位，我们建议对基于SOM的解决方案使用大数据分析。该提案旨在1)应用技术以实现有效的数据收集和分析，2)构建特定于SOM的分析和利用这些分析的模型，以实现对用户活动的有效检测，以及3)为提取分析的无缝反馈提供界面和用户体验设计。拟议的项目旨在针对一个很大程度上研究不足的领域，即如何最好地利用大数据分析和人机界面来改善SOM应用的决策。已完成研究的潜在结果将对行业和研究产生影响。对于工业来说，我们的研究将带来更好的SoM技术，这不仅是由硬件进步驱动的，也是由数据和智能分析驱动的。对于研究界，我们拟议的研究将引领SOM的大数据分析领域，据我们所知，这一领域在很大程度上仍未被探索。除了具有原创性，这项拟议的研究也是及时的，因为据预测，可穿戴技术将改变许多领域的未来，包括体育、医学、导航甚至购物。

Wearable devices are becoming increasingly popular and are estimated to reach 245 million units and be worth 25 billion dollars by 2019. To enable the rapid advancement of wearable devices for a variety of applications, system-on-module (SoM) solutions have been proposed. As SoM solutions become more powerful and prominent, they are playing a more intelligent role, and are being used in various applications such as sports training and rehab/therapy. Hence, SoM stakeholders are in need of analytics to improve the decisions made based on their solutions.To advance the state-of-the-art and keep Canadian manufacturers of SoM technology in the forefront, we propose the use of big data analytics for SoM-based solutions. The proposal aims to 1) apply techniques to enable effective data collection and analytics, 2) build SoM-specific analytics, and models that leverage these analytics, to enable the effective detection of user activities and 3) provide interface and user experience design for seamless feedback of extracted analytics. The proposed project aims to target a largely under-researched area, which is how to best use big data analytics and HCI to improve decision making for SoM applications. The potential outcome of the completed research will have impact on both industry and research. For industry, our research will lead to better SoM technology that is not only driven by hardware advances, but also driven by data and intelligent analytics. For the research community, our proposed research will spearhead the area of big data analytics for SoM, which to the best of our knowledge remains largely unexplored. In addition to being original, the proposed research is timely since it is projected that wearable technology will transform the future of many fields, including athletics, medicine, navigation and even shopping.