The Perception layer in Internet of Things (IoT) architectures is responsible for connecting sensor nodes and data acquisition units such that sensing devices capture relevant data from the corresponding environment. Most IoT platforms are designed to transmit data at fixed time intervals, which is a disadvantage in the modern world dominated by rapid changes in the evolution of events. This paper addresses improvements performed on an IoT platform dedicated to critical applications (e.g., fire, air pollution). This novel approach assumes the use of two equations empirically determined to compute the time interval between successive transmissions depending on the detected event. A new method for communication technology selection (LoRaWAN, Wi-Fi or cellular) is implemented and the time interval between two successive transmissions is adjusted according to the occurring event. Comparisons were highlighted for each analyzed case. The proposed method proved to be suitable for critical scenarios or scenarios that can generate false-positive alarms, due to abnormal variations of parameters.