Combining Mobile Crowdsensing and Wearable Devices for Managing Alarming Situations

Dangerous events such as accidental falls, allergic reactions or even severe panic attacks can occur spontaneously and within seconds. People experiencing alarming situations like these often require assistance. Modern wearable devices such as smartphones or smartwatches can be used to detect these situations by utilising the plethora of sensors built into them. Mobile Crowdsensing Systems (MCS) might be used to manage the detected alarming situations. To handle these events, an MCS requires integration with mobile sensory devices, as well as the voluntary participation of people willing to help. The contributions of this paper are twofold. First, we enhance the capabilities of an MCS by enabling the integration of various Bluetooth wearable devices. Second, we perform a simulation that models different scenarios that represent dangerous events. Through the MCS simulation, we identify essential parameters that need to be considered when building such a system. The simulation can also be used to find the optimal configuration of the MCS.