AGILE project aims to create an open, flexible and widely usable IoT solution at disposal of industries (startups, SMEs, tech companies) and individuals (researchers, makers, entrepreneurs) as a framework that consists of:
- A modular IoT gateway enabling various types of devices (wearables, home appliances, sensors, actuators, etc.) to be connected with each other and to the Internet
- Data management and device control maximizing security and privacy, at local level and in the cloud, technologies and methodologies to better manage data privacy and ownership in the IoT
- Support of various open and private clouds
- Recommender and visual developer’s interfaces enabling easy creation of applications to manage connected devices and data
- Support of mainstream IoT/M2M protocols and SDKs from different standardization bodies for device discovery and communication
- Two separate gateway hardware versions: a) the ‘maker’s’ version, based on the popular RaspberryPi platform for easily prototyping and attracting the current community; b) the ‘industrial’ version for more industrial and production-ready applications
- An ecosystem of IoT applications shareable among users and developers leveraging on existing initiatives by key stakeholders in this domain, like Canonical and Ubuntu Snappy IoT ecosystem.
Piloted in relevant open areas (fields and in a port) for field & cattle monitoring through drones, air quality & pollution monitoring and in smart retail, AGILE will be easily adaptable and usable in different contexts serving as an horizontal technology for fast IoT prototyping and engineering in different domains. Following an open hardware/software approach, harnessing the power of IoT developers and entrepreneurs communities, AGILE aims to offer tools to overcome limitations imposed by closed and vertical walled gardens for IoT apps development, offering a fully open platform for integration and adaptation with 3rd parties enabling a new marketplace for IoT apps
BioAssist aims through the participation in the AGILE to enrich the existing home care platform with the Quantified Self concept. By exploiting the communication and extensibility features of the existing platform, the real-time analysis algorithms will be fused with data from various sources such as biosignal measurements, proximity sensors and also historical data from user’s record so as to provide continuous assessment and also to detect anomalies and emergencies (e.g. detect potential for obesity, detecting inactivity that can be linked to diseases, potential falls exploiting the smartwatch data or behavioural changes).