Most of existing indoor navigation systems work in a client/server manner, which needs to deploy comprehensive localization services together with precise indoor maps a prior. In particular, an iOS-based prototype with Arduino wearable devices and static iBeacon nodes is implemented to verify the feasibility and correctness of our iBaby system.

To accurately detect stranger holding behaviors, multi-feature based, artificial neural network based, and convolutional neural network based posture recognition methods are designed to improve recognition success rates of iBaby as much as possible. In the finding mode, the iBaby system can cooperatively find missing children equipped with hand wearable devices consisting of the mobile iBeacon and 3-axis accelermeter through crowdsourced sensing networks formed by smartphone users with outdoor GPS and indoor IoT localization. In the monitoring mode, the iBaby system can prevent young children from taking away by strangers/people with bad intentions. This paper designs and implements a mobile children monitoring and finding system, called iBaby, using wearable devices and nearby smartphones to detect unexpected holding and find missing children through Internet of Things (IoT) technologies, respectively. Experimental results show that CCMF outperforms existing methods and can significantly increase recognition success rates and efficiently reduce false alarm rates of holding up detection. An iOS-based prototype with Arduino wearable devices and mobile/static iBeacon nodes is implemented to verify the feasibility and superiority of our framework. According to our review of relevant research, CCMF is the first children monitoring and finding solution that can detect holding-up postures of a target child and provide the guiding path to a lost child through crowdsourced sensing networks.

In the finding mode, the CCMF framework can cooperatively find missing children equipped with wearable devices consisting of mobile iBeacon and 3-axis accelerometer modules through crowdsourced sensing networks formed by smartphone users with outdoor GPS and indoor IoT localization. In the monitoring mode, the CCMF framework can prevent young children from taking away by strangers/people with bad intentions. In this paper, we propose a crowdsourced children monitoring and finding (CCMF) framework to detect holding-up behaviors and find missing children using wearable devices and surrounding smartphones based on Internet of Things (IoT) technologies.

Satgear easyfind system