Enhancing the Quality of User Research Using Embedded IoT Sensors for Collecting Life Information

Abstract

This study aims at developing a new user research method that uses IoT sensors embedded at users' homes to enable users to recall their memories. The proposed method was evaluated by experiments where four participants individually created user journey maps with quantity data that was collected for seven days. The results showed that IoT sensor data increased the quantity, clarity, and accuracy of recalled memories. This study argues that IoT sensors can be an effective approach to increasing user research quality by triggering users' memories without interfering with users' ordinary lives.

Designers’ perceptions of a sensor-enabled diary method for enhancing user research

“…Interestingly, sensors attached to shelves elicited 37 % of the self-reports having diversified contents, while sensors on microwaves mostly drew self-reports on eating meals. In an experiment where subjects of user research utilized sensor data for recalling memories afterward, the frequently used objects are not good sources for recalling memories (Tanaka et al, 2022). The results suggest that frequently used objects are good sensor data sources in asking for self-reports in the users' lives.…”

“…Sensor data may be ethically more acceptable, while data itself has less information than camera-based methods. Behavioral data can objectively acquire and graphically visualize users' specific behavior, while a single sensor can only collect limited users' behavior and lacks holistic visualization of users' behavior (Tanaka et al, 2022). Gorkovenko et al (2023) tested the behavioral data from multiple devices and pointed out that qualitative data from users is also essential to elicit insights on users when making sense of behavioral data.…”