AN OPEN IOT PLATFORM FOR INTELLIGENT ENVIRONMENT MANAGEMENT THAT IMPROVES OPERATIONAL EFFICIENCY AND MAKES THE CUSTOMER EXPERIENCE INCREASINGLY PERSONALISED
At a time when everything is hyper-connected, even the management of environments in the various contexts of home, office and production can be made much more efficient through customised intelligent automation systems. SCAI Lab has developed a SMART “COGNITIVE” AUTOMATION platform, which integrates virtual objects plus other specially developed agents to rapidly implement Smart Home/Smart Office/Smart Health/Smart Production services.
The aim is twofold: on the one hand to increase operational efficiency in building automation, and on the other hand to make the digital experience more customer-friendly.
In this vision, the spaces (homes, offices, hospitals) are rethought as self-sufficient, functional and effective organisms in their own environment, through processes of continuous self-learning and real-time self-organisation.
Cognitive spaces support a network of sensors that are strategically placed within a space. Unlike automated buildings, this network is coordinated by an intelligent system that receives and processes information through the use of cognitive computing and big data processing techniques.
The platform is able to optimise the use of specific areas of living and working spaces so that there are no unused or unsafe spaces, and automate the organisation of indoor and outdoor environments (e.g. access control, smart parking with online booking systems, liveability of hospital environments). Just think about the possibility of making home environments more ‘liveable’ to provide a personalised level of care for the elderly or valuable information for carers.
The integrated management of the IoT network is based on a distributed and decentralised IT architecture: an Edge Computing architecture consisting of a network of choreographed autonomous agents, capable of storing and processing critical data locally and only transmitting it (if necessary) later to a central data centre or cloud storage repository.
The system represents a paradigm shift in the Internet of Things and in mobile business applications, improves application usability and removes workflow barriers for mobile and multi-channel process automation scenarios.
The system also requires minimal resources (Raspberry, mobile devices with Mac OS X/IOS, Android, WP and Windows).
The advantages of using an edge computing architecture over a conventional cloud model include overcoming the latency, reliability and bandwidth issues that make these standards less efficient.
The design of such a solution is based on three main layers.
– Iot Edge Platform
– Machine Learning modules
– Blockchain for data certification
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