This work targets the exploration and development of a new IoT platform, LACE-Net, for bridging users with their environments and each other. As such, it considers:
a) how to display information to users and allow for fluent user interactions in IoT spaces;
b) how to maintain trust and privacy between users of IoT information in their interactions; and
c) how to apply these designs for effective user to user interaction, coordination, and collaboration in IoT environments, while gauging the dynamics of IoT organizations in action.
The potential use cases of the adaptive and privacy elements of IoT are vast, impacting varied stakeholder domains. With the combined perspectives of users, groups of users, and the overall IoT system, managers of IoT deployed systems of all kinds can gain valuable insights that can have an impact on policy-making and governmental decisions. Such a system can have an impact on mitigating the number of information silos within organizations by allowing for multi-level collaborations to be formed.
The Internet of Things refers to the addition of both computation and connectivity devices to existing objects in the environment (this includes human users in the environment, as well as other kinds of actors); allowing for new forms of communication and interaction. Making things “smarter” by embedding sensors, actuators, and a control unit (to makes sense of incoming information and corresponding actions) opens the door for adaptive ambient intelligent behaviors, which can be as simple as dynamic heating, lighting, and ventilation when a person enters a room, or when a user requests a remote-interaction with their home from an online service that turns on appliances in their environment. It can also be as complex as driver assistance for self-driving vehicles, and user attention modeling and interaction. The potential applications are many. This project investigates platforms, and architectures for the development of IoT systems that will be applied to future projects.
Transforming the way people interact with everyday technologies requires approaches for an adaptive Internet of Things.
This ongoing project space hones in on the question of how to introduce artificial intelligence for personal context-based adaptive and assistive interfaces, and how to maximize the value of such systems to users. Advancing this work considers a mixture of methods, several of which includes technology development related to exploration of a human-centered approach to IoT.
Privacy in the Internet of Things, due to the inherent need to collect and share large sets of personal, sensory data, is essential, and is a present and clear challenge. Research is needed to ensure that the sensitive information being obtained is safely and securely handled, designed, and distributed. This is a significant research challenge and has an impact that is cross institutional, governmental, and global-impacting, for both individuals, organizations, and groups. This work aims to address this challenge with a new privacy-enabled IoT approach, particularly for adaptive IoT.
The IoT adds a revolutionary layer of networked physical devices and intelligent environment services to the web-based client-server internet of computers and smartphones. As IoT deployments become commonplace, with many devices, users will inevitably face challenges in understanding and interacting within smarter, complex, and dynamic environments while using traditional information system interfaces and also focusing on active tasks. IoT information ecosystems need technologies that understand situations and present contextually relevant user interfaces. This ongoing project aims at immersive interfaces for context management systems in IoT and prototype experimentation toward future human-aware, adaptive, and immersive environments.