The aim of this project is to help developing and nurturing Smart Tourism in Edinburgh and the South-East Scotland City Region (1.3 billion pounds and 30,000 jobs in this sector - ETAG, 2016) by developing new tools for capturing and understanding visitor flow within and among the many attractions. The project focuses on visitor attractions because they are a substantial component of the visitor economy and it will be partnering with local stakeholders to help them take advantage of Smart Tourism. In general, such attractions are charitable institutions or small to medium enterprises with no or limited capacity for data analysis and without a culture of data sharing. Consequently, decisions are made without access to data insights making it difficult to plan and undertake effective marketing, predict future customer flow or analyse how visitors use the physical environment. However, with data collection and sharing, comes privacy concerns. The General Data Protection Regulation (GDPR), protects citizens but also creates an entry barrier for personal data use. Therefore, this project will explore ways to anonymise data directly on the sensor device (“the edge”), guaranteeing it is not possible to uniquely identify a person, consequently being fully compliant with GDPR in a cost-effective way while still delivering statistical information to fulfill the smart tourism aims.
I submitted the project proposal and I was selected for one of the only 25 TRAIN@Ed MSCA Research Fellowships at University of Edinburgh. During the time I worked in this project I developed a small smart camera capable of running complex computer vision algorithms (e.g. object detector, skeleton detection, license plate recognition) that could run on less than 2W called Maple Syrup Pi Camera.