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Machine Learning for Object Prediction in Station-of-Things Environment

This paper put forwards the concept of Station-of Things (SoT) for identifying different vehicles types which are present in parking slot using Machine Learning (ML). The study in this paper uses the concept of Internet-of-Things (IoT) to represent a station (parking lot) containing a thing of interest (car) which can be homogeneous or heterogeneous, and is termed as SoT. Advanced research in communication, computation and sensors innovation has enabled to build intelligent SoT environment. SoT environment refers to a station containing an object or a thing of interest. This can be anything from occupancy of chairs in a study hall, vacant seats in auditorium, cars parked in parking-lot, books on a bookshelf, and so forth. Similarly identifying different objects like vehicles in parking slot, goods in warehouse, different furniture in furniture showroom, in above three mention situation different objects are of different dimensions but same system can be applied for prediction of objects by changing the dimensions of object in database of ML toolkit.