Abstract
We present the technologies and the theoretical background of an intelligent interconnected infrastructure for public security and safety. The innovation of the framework lies in the intelligent combination of devices and human information towards human and situational awareness, so as to provide a protection and security environment for citizens. The framework is currently being used to support visitors in public spaces and events, by creating the appropriate infrastructure to address a set of urgent situations, such as health-related problems and missing children in overcrowded environments, supporting smart links between humans and entities on the basis of goals, and adapting device operation to comply with human objectives, profiles, and privacy. State-of-the-art technologies in the domain of IoT data collection and analytics are combined with localization techniques, ontologies, reasoning mechanisms, and data aggregation in order to acquire a better understanding of the ongoing situation and inform the necessary people and devices to act accordingly. Finally, we present the first results of people localization and the platforms’ ontology and representation framework.
Highlights
The Internet of Things (IoT) is becoming more and more popular and its applications are facing an enormous proliferation resulting in a new digital ecosystem
The proposed system architecture consists of three basic layers: (i) the Hardware layer which consists of the mobile devices, the sensors and the actuators, (ii) the Middleware layer that supports the easy interaction with the edge components and is responsible for managing the communication between the two edge layers of DESMOS, and (iii) the DESMOS platform (Data Aggregator, crawlers and databases), a cloud based layer that is used for storing, processing of the collected data, and generation of reports that will be sent back to the Middleware
We suggest some statistical filters in the paragraphs, in order to improve the stability of the received signal strength indication (RSSI) values and some machine learning techniques to find the distance from the RSSI values
Summary
The Internet of Things (IoT) is becoming more and more popular and its applications are facing an enormous proliferation resulting in a new digital ecosystem. People are evolving as an integral part of the IoT ecosystem, interacting with processes, data, and things driving the evolution toward a ubiquitously connected world with immense possibilities In this new realm, novel concepts and methods are needed to infuse and transform human awareness into situation awareness, support smart links between humans and entities on the basis of goals, and to adapt device operation to comply with human objectives, profiles and privacy. In order to realize the above-mentioned goals, the platform follows a systematic approach for interconnecting people, services, and devices using: (a) applications in mobile and wearable devices that will be used by volunteers, citizens and local authorities, (b) smart spots able to listen for reports and request for help and further propagate them in the local intelligent network, and (c) fusion and interpretation of heterogeneous events and information through semantic reasoning and decision-making.
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