Results - Stage 2

• A multi-tier architecture of an IoT platform, named EMULSION, has been elaborated as a representative of the new generation of IoT platforms of horizontal type.
• Implementation of the platform has been realized by integrating various (low-cost) electronic modules and (open-source) software components, following the essential engineering principles for achieving the required interoperability, in order to effectively deliver various types of personalized and contextualized IoT services over heterogeneous (wireless) communication networks, and efficiently support software applications using cloud structures, anytime–anywhere–anyhow in accordance with the ABC&S paradigm for always best connected and best served users. Working models of various IoT services have been developed as well.
• Stable and optimal functioning of the EMULSION IoT platform has been achieved when using different user devices, sensor sets, monitoring stations, communication modes, data processing algorithms, operating systems, etc., under different operational conditions and for achieving different tasks over a long period of time with performed complex (and high!) evaluation of its performance.
• A wide range of scenarios, use cases and application areas of the developed platform has been implemented and demonstrated through various prototype systems created on its basis, functioning in the IoT areas of "smart environment", "smart healthcare", "smart infrastructure", "smart water supply", "smart home", etc.
• In particular, for the first two IoT areas, a stable and reliably functioning AQI pilot system has been created with a corresponding software application for generating and recommending the "healthiest" travel route for patients through areas with polluted atmospheric air, i.e. a route possessing the lowest risk to the health of the respective user-patient. The idea of ​​a "healthiest" route was developed and proposed by the project leader, Prof. Ivan Ganchev, and disseminated by him as part of the project activity in the form of various scientific papers and reports (including 2 plenary reports, 3 keynote reports, 1 invited report, and 2 regular reports), presented mainly at international conferences.
• Multiple successfully functioning AI models with machine learning have been developed for use by the EMULSION platform in providing uHealth services to users in the IoT area of ​​"smart healthcare".
• A new vision has been proposed for highly personalized and contextualized recommendations of services (in real time) to mobile users, taking into account the current context. An entire system architecture has been elaborated, which generates and dynamically handles user profiles for facilitating and optimizing the process of discovering and recommending services to users in order to achieve the best quality of service (QoE). New effective and efficient models for intelligent service recommendation have been developed.
• A set of novel models has been developed for the analysis and short-term prediction (depending on weather conditions, atmospheric factors, etc.) of air pollutions in order to prevent (and report in case of) exceeding the allowable thresholds.