Integrating building automation system into integrated danger management system

OData support
Supervisor:
Braun Patrik János
Department of Automation and Applied Informatics

Nowadays building automation systems are surrounding us at shopping malls, office blocks, university buildings, and yet they starting to gain space in our homes as well. Using them, we can achieve significant energy efficiency improvement, moreover, they make our life easier and more comfortable, so they help us to focus on doing our job.

KNX is a communication protocol for building automation systems. Supporting it is the primary purpose of this project, because it is simple, efficient and vendor independent.

Within the scope of my thesis, I extended the Siwenoid IDMS (Integrated Danger Management System), which is written in Java language. The purpose of my work was to make it possible, to cooperate not only with security and safety systems, but building automation as well.

With the implementation of data point type handling and importing, commands and treatments (binds data point values to signals) can be connected to them. Making the usage of KNX data points (e.g. sensors, switches) with similar behaviour comfortable. Implementing two-way communication between the application and KNX devices made possible to monitor and send values (commands). Using scanned values, signals (e.g. alarm, warning) can be generated, which form the basis of the danger management system. Moreover, they can be visualized on a map or line chart to make current and past data traceable. The system also uses signals as a trigger to automatically notify authorized users per SMS or e-mail. Thanks to data point aggregation, it is possible to merge multiple data points by providing logical functions between them. For example, it is not important to handle each light separately, making groups of them and handle signals from the groups is a better solution (e.g. is every light working). This aggregation makes the system easier to use, since it provides a better overview. My solution also supports command scheduling. It sends the given commands to data points periodically on the given day(s) of the week.

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