Pest and disease identification in plants is a common problem faced mostly by farmers with critical direct impact on production of food and consequently negative impact on the environment and eventually on human well-being trough the use of pesticides. The first step is to have a proper diagnostic preferably at an early stage. Pest and disease diagnostics are sought by farmers either by talking with each others, by calling a specialist or by sending plant samples to certified laboratories for analysis. Respectively, these ways seem to be ineffective, not be readily available (or not available at all) or take longer than needed. OpenPD, an on-the-field and on-the-fly system for fast identification of plant pests and diseases, aims to provide a way to shorten the response time for a correct diagnostic of plant and crop pests and diseases by speeding up the process of identification. Supported by a database and a mobile app, users submit a digital photo of the affected plant part along with other relevant data and receive an answer leading to the diagnosis, coming from other users (general or specialists) or automatically by image interpretation and/or by a learning algorithm taking previous (positive) users answers. OpenPD will be reactive (users’ questions and answers) but also proactive (sending warnings and alerts to users) and will be structured as an open community model. Answers should be evaluated and users rewarded and ranked using a ranking pyramid model (evaluation by the users but also by the system). OpenPD will make use of at least 6 generic enablers from the FIWARE Catalogue and be integrated in FISpace. OpenPD’s business model customer acquisition component will by supported by its Freemium model, strategic partnerships with public and private organizations, media partnerships and digital media plan. The monetization component will have its support on sponsorship, paid subscription fees and report generation from data mining the database as it grows.