WP1: Establishment and implementation of a project management and quality assessment plan, progress reporting, monitoring of compliance of ongoing studies with ethical guidelines, preparation and submission of ethical applications; WP2: Identification of the user requirements, usages scenarios and business processes, along with the specification of the data collection and medical evaluation protocols governing all phases of data collection and system evaluation during the project lifespan; WP3: Design and implementation of data acquisition and protection methods for G/SData and Intervention phases, development of Smart Belt, implementation of G/SData analysis and machine learning algorithms, collection of big real-world data, evaluation of the effectiveness of G/SData analysis components; WP4: Design and development of a Personalised Game Suite (PGS), design of the Targeted Nocturnal Intervention (TNI), design and development of Voice Enhancement (VE) and Gait Rhythmic Guidance (GRG) interventions, development of PD-related behavioural models, development of PGS adaptation algorithms; WP5: Establishment of the Cloud-based i-PROGNOSIS data management infrastructure, realisation of the i-PROGNOSIS mobile applications (i.e. iPrognosis and iPrognosis Wear) for acquiring data from the everyday use of smartphone and other wearable devices, design and development of the interventions web-platfor, production of an Open Data Management Plan; WP6: Pilot data collection before G/S/IData studies, G/S/IData collection studies implementation, definition of the medical evaluation protocols, medical evaluation of the i-PROGNOSIS system in terms of PD symptoms detection, medical evaluation of the interventions; WP7: Design of detailed and holistic assessment plan and evaluation methodology, technical assessment and user acceptance evaluation of the iPrognosis and iPrognosis Wear apps and interventions, MAFEIP-based impact assessment of the interventions WP8: Scaffolding of social awareness via dissemination activities towards the construction and growth of i-PROGNOSIS community and network of stakeholders, dissemination of scientific results, development of detailed exploitation plan and intellectual property rights identification. The described workload and results, clearly support the three basic pillars of i-PROGNOSIS, i.e. PD early detection, novel PD-related interventions and social responsiveness to participation, data donation and PD awareness. The aforementioned work resulted to the following main outcomes: i) smartphone and smart watch applications for unobtrusive behavioral data collection, ii) machine learning algorithms for PD symptoms detection, iii) PGS and assistive interventions.