INTELLIGENT LIVING IN SMART SOCIETY (HOMEHERO)
The prevalent integration of the smart devices and wearable technologies into people lives that measure the daily health and activeness has been proliferated in recent years. The potential integration of biometrics, behaviors, and other health data collected by smart devices into medical repositories offers new possibilities to health experts and a powerful tool to improve our everyday life. The technical challenge to connecting this daily activity data to public health data is to build a common bridge between them that minimizes the efforts/costs of institutions to access the data, and expands their ability to connect to the individual’s daily data. This problem generalizes to researchers outside the medical field as well, as health and fitness devices are part of an Internet of Things(IoT), but challenge remains the same. Home Hero is a smart home IOT gateway offering this bridge to connect public health data to individual wellness information.
Home Hero has been conceptualized and developed by a
team at Louisiana Tech as a device agnostic solution to
consolidate the information generated by personal IOT smart
devices. However, the challenge proposed here includes
heterogeneity of smart devices and their protocol, volume
and velocity of the data, induvial privacy as well as the
interoperability with public health systems. In addition, our
objective is to further develop a model that scales to city or
state-wide levels and build Home Hero with the ability to
easily adapt to new technologies and standard/ upcoming
protocols such as HL7, GPID, while creating a methodology
that preserves user privacy and security. Furthermore, the Home Hero efforts expand into directly enabling healthier and smarter living through a system to inform users of the nutritional value of their food which will be expanded to generating suggestions based on dietary restrictions.
BIO-INSPIRED ADAPTIVE MOTOR CONTROL AND AUTONOMOUS LEARNING
The insect brain is a very efficient neural computing system.
It can process high-dimensional sensory information and generate
coordinated and adaptive motor commands in real time,
resulting in various complex behaviors (including locomotion, object
manipulation, navigation, and their combination). Simultaneously,
it can also autonomously learn to solve complex tasks. This amazing
control performance is achieved by using the full capacity of its neural
dynamics, learning, memory, and plasticity as well as by interacting
with the environment through its body (i.e., embodiment).
Inspired by this, we have developed brain-like mechanisms. The mechanisms are based on a modular concept and hierarchically organized. They exploit neural dynamics, learning, memory, and plasticity, as the biological brain does, to efficiently generate complex functions of embodied multi-sensorimotor robotic systems. Based on
this development, we have addressed the way to achieve adaptive motor control and autonomous learning principles for complex locomotion, object manipulation, goal-directed navigation, and their combination in the embodied systems.