Mobile technologies have been providing noteworthy scenarios regarding elderly care, replacing the traditional phone calls and face-to-face caregivers by a myriad of sensors and communication networks supporting detailed activities monitoring. On the other hand, the recent COVID pandemic has been leading governments to adopt contact tracing apps aiming at controlling the virus spreading. However, that adoption has raised many legitimate issues regarding individual privacy, besides those related to the effectiveness of this kind of app. In this context, this paper presents FenceBot, a novel approach for safety monitoring of the elderly when outdoors. The elderly data are kept private whenever in normal conditions, and alerts are sent to relatives only on unsafe or contagious risk situations that would demand verification and actions. The proposed technology was evaluated with a discrete-event simulation and the outcomes provided a solid indication of its effectiveness regarding protection from contagious risks situations.

The evidence-based software engineering approach advocates the use of scientific evidence by software engineers to support the adoption of software technologies in industrial software development and maintenance projects. Aside from the unavailability of scientific knowledge in industrial settings and the time required to acquire evidence in the software engineering (SE) field, additional challenges prevent practitioners, mainly those that are not experienced in research, from collecting knowledge from scientific sources to support the decisionmaking throughout their software projects.