Techniques for eliciting IoT requirements: Sensorina Map and Mind IoT

Abstract

Context:

The Internet of Things (IoT) involves heterogeneous devices that interact and process data via the Internet. In the development of IoT systems, requirement elicitation is crucial. However, challenges such as heterogeneity, interoperability, scalability, and requirements volatility necessitate new approaches or adapting traditional techniques.

Objective:

In this context, this work proposes the Sensorina Map and IoT Mind as techniques adapted from the Empathy Map and Mind Map, respectively, to support requirement elicitation in IoT systems.

Method:

Two empirical studies were conducted in an academic environment to assess the feasibility of the techniques, then, a case study in industry environment.

Results:

The first study analyzed the ease of use and evaluated if it assisted software engineers in remembering the system requirements. The participants’ perceptions were collected through a Focus Group, refining the techniques. Subsequently, an observational study evaluated the techniques’ usefulness and ease of use. The results of the study demonstrated that the participants considered the methods feasible. The case study results revealed that the Sensorina Map is more suitable for advanced stages. At the same time, the Mind IoT suits better the initial phases, emphasizing the need for practical examples and adaptations to suit diverse user profiles.

Conclusion:

This work is expected to advance research in IoT systems and benefit professionals and researchers in this area.