Effectivizing tag interpretation in IoT

Abstract: Home automation systems is something that has risen in popularity over the last decade. More and more real estate is equipped with various IoT systems in order to keep effective- ness and efficiency on a high level. With these systems comes highly advanced technical systems connected to various devices that report data collected from their environments. The data that is collected is then reformatted into tag lists in the software with a very specific name that follows a certain naming convention. The problem is that there is no transparency amongst companies when it comes to the standards they follow when it comes to naming their tags. This is investigated in this thesis by conducting a literature review and creating a design to interpret existing tag lists to make it easier to understand the structure. The thesis is made with the intent of answering the question to what the current state of research when it comes to standardization in tag lists. It is also exploring what a potential effective design for translating tags into a manageable format would look like. At the time of making this thesis there were not very extensive research when it comes to standards and naming convention in IoT tag lists, therefore a lot of the compiled research in this thesis refers to related ways of structuring names in other topics. The design was developed with the help of an scale-up company called Sensative that works with IoT tags on a daily basis. The end result of the design is a translation service that is able to sugges- tion relatable tags to translate when a user is manually renaming tags that are imported into the service. The design is built with the potential to later add artificial intelligence to suggest related tags for translation.