Abstract. In recent times, people have become concerned about their environmental conditions, amid deteriorating global statistics on bad air quality, global warming and UV light exposure. Conventional technologies for reading environmental conditions are expensive, bulky and situated, yet, people are mobile and need portable tools to be aware of their immediate environmental conditions on demand. Smartphones are now widely used, endowed with sensors and wireless communication technologies such as Bluetooth, and Near Field Communication (NFC) for external sensor connectivity, making smartphones a viable tool for fingerprinting the environment. This thesis outlines the design, evaluation and implementation of a mobile-enabled system for environmental data collection using a portable NFC powered sensor board. The name of the system developed in this thesis is the S3 system.
The S3 system is a two-tier system which consists of S3 Android application and an online dashboard with a data repository. The S3 Android application is used for collecting and visualising environmental data; temperature, humidity, UV, ambient light, with a smartphone and a credit card-size NFC powered sensor board. The sensor data is then periodically synced to the online data repository. Additional features of the S3 application include automated feedback sampling, introductory tutorial, and user preference settings. The thesis further details the design and implementation process with scenarios, use cases, paper sketches, expert review of sketches, interface mockups, evaluation of prototype with a user study, quantitative and qualitative analysis of user study data, and finally the implementation of the S3 application. The thesis also presents a test run to demonstrate the capabilities of the S3 system as a mobile-enabled solution for crowdsourced environmental fingerprint datasets.
To the end user, the work in this thesis provides the S3 application and the NFC powered sensor card as a portable tool for personalised environmental fingerprinting. On the other hand, the intervention in this thesis will have an impact on research since the crowdsourced environmental fingerprint datasets can be valuable datasets for research. As a TEKES project, the solution also provides a proof of concept for further improvement and deployment into the commercial software market
