Bluetooth mesh is a recent technology built on the Bluetooth low energy protocol stack architecture, focusing on the Internet of Things. It represents an excellent solution for commercial and industrial lighting applications, though it is still evolving. One of the biggest challenges of the Bluetooth mesh network is the improvement of confirmation messages reception. In a Bluetooth mesh network, determining the Status of the received messages is a critical aspect that can generate unexpected issues when multiple devices respond simultaneously, as it may occur in some lighting applications. This behavior can reduce the probability of message delivery due to collisions, especially when the number of devices in the network increases. This article aims to improve the reliability in receiving confirmation messages in a Bluetooth mesh network by proposing a new technique of spreading Status overtime. To evaluate the proposed technique’s performance, we compare our technique with a Bluetooth mesh network with standard configuration (SC) using real nodes experimental setup. We evaluated our results in terms of packet-loss rate, obtaining 98.84% of the Status received for the network with our optimized configuration and 96.98% for those with the SC. Finally, an in-depth performance evaluation method for the analysis of the lost Status was also conducted.

Sleep is extremely important for physical and mental health. Although polysomnography is an established approach in sleep analysis, it is quite intrusive and expensive. Consequently, developing a non-invasive and non-intrusive home sleep monitoring system with minimal influence on patients, that can reliably and accurately measure cardiorespiratory parameters, is of great interest. The aim of this study is to validate a non-invasive and unobtrusive cardiorespiratory parameter monitoring system based on an accelerometer sensor. This system includes a special holder to install the system under the bed mattress. The additional aim is to determine the optimum relative system position (in relation to the subject) at which the most accurate and precise values of measured parameters could be achieved. The data were collected from 23 subjects (13 males and 10 females). The obtained ballistocardiogram signal was sequentially processed using a sixth-order Butterworth bandpass filter and a moving average filter. As a result, an average error (compared to reference values) of 2.24 beats per minute for heart rate and 1.52 breaths per minute for respiratory rate was achieved, regardless of the subject’s sleep position. For males and females, the errors were 2.28 bpm and 2.19 bpm for heart rate and 1.41 rpm and 1.30 rpm for respiratory rate. We determined that placing the sensor and system at chest level is the preferred configuration for cardiorespiratory measurement. Further studies of the system’s performance in larger groups of subjects are required, despite the promising results of the current tests in healthy subjects.