Multi-sensor Fusion and Signal Processing for Massive Amount of Data

高分辨率传感器广泛应用于各种应用，如环境监测、医疗保健、工业控制、汽车系统和智能移动设备。随着综合数据池的可用性迅速增加，分析从各种来源获得的数据以提取有用信息的趋势日益增长。利用大量异构数据集的可用性来更好地了解各种问题是我们当前的研究目标之一。然而，真实数据需要计算预处理、频繁访问、数据存储和安全问题。除了算法方面的挑战，普遍缺乏强大的计算框架和合适的数据存储和共享手段，这减缓了我们正在进行的项目，并阻碍了我们实施新的想法。

High resolution sensors are utilized in a wide variety of applications such as environmental monitoring, healthcare, industrial control, automotive systems and smart mobile devices. As the availability of comprehensive data pools increase rapidly, there is a growing trend in analyzing data acquired from various sources to extract useful information. Exploiting the availability of massive heterogeneous data sets to gain better insight on a wide range of problems is one of our current research goals. However, real data comes with a need for computational preprocessing, frequent access, data storage, and security concerns. Alongside algorithmic challenges, the general lack of powerful computational frameworks and a suitable means for data storage and sharing have decelerated our ongoing projects and deter us from implementing new ideas.