Due to the growth of the Internet and the device diversity together with their communication capability the Internet of Things (IoT) is a hot topic. The Internet of Things is not limited to Peer-to-Peer (P2P) networks and devices like server, computers, and routers any more. It also includes wireless sensor devices connected in a Wireless Sensor Network (WSN).
The application range goes from intelligent homes, logistic, health care to environmental monitoring. All applications have in common a hugh amount of collected sensor data (e.g., temperature, brightness, humidity). In general this data is stored in a data base and accessible by authorized users for further analysis. One case of analysis is the value development over time. The simplest way to visualize this development is to plot the data in curve diagrams. This can be done using online solutions like Xively or offline solutions (e.g., Matlab, JPGraph). Each solution has advantages and disadvantages that must be taken into account when developing a visualization solution depending on a special application.
The task of this assignment is threefold. First, the integrated visualization of Xively in SecureWSN must be analyzed in order to find the used interfaces and to understand the data upload to Xively. Second, existing offline solutions must be analyzed concerning their functionality compared to Xively. In the third step, one offline solution should be selected, implemented according to Xively functionality and integrated into the existing environment of SecureWSN, especially in CoMaDa (optional is integration into WebMaDa), re-using existing data formats (like JavaScript Object Notation (JSON)) and interfaces.
The developed offline visualization solution will be tested with WSNs with different settings (e.g., network size, sample rate, duration). The received visualization is compared with already implemented Xively. Important is that for each sensor type (e.g., temperature, brightness, humidity) one curve dia- gram is available and that the user can specify the viewing period (e.g., last 10 minutes, time period from 5 a.m. to 3 p.m.). The latter becomes important if a WSN runs for a long period and the user is interesting for short periods.
The result of this assignment is an offline visualization possibility for sensor data with same func- tionality as Xively offers. The overall goal is to make the user independent of any online tool for data analysis.
Supervisors: Lisa Kristiana, Dr. Corinna Schmitt
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