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The foundation of the Internet of Things (IoT) consists of different devices, equipped with sensors, actuators and tags. With the emergence of IoT devices and home automation, advantages from data analysis are not limited to businesses and industry anymore. Personal analytics focus on the use of data created by individuals and used by them. Current IoT analytics architectures are not designed to respond to the needs of personal analytics. In this paper, we propose a lightweight flexible analytics architecture based on the concept of the Kappa Architecture and microservices. It aims to provide an analytics platform for huge numbers of different scenarios with limited data volume and different rates in data velocity. Furthermore, the motivation for and challenges of personal analytics in the IoT are laid out and explained as well as the technological approaches we use to overcome the shortcomings of current IoT analytics architectures.

A Personal Analytics Platform for the Internet of Things - Implementing Kappa Architecture with Microservice-based Stream Processing