The population of the Chinese white dolphin is claimed to be critically endangered and is on the International Union for Conservation of Nature (IUCN) Red list. It is estimated that there are fewer than 100 individuals in the East Taiwan Strait, and the number is falling. The dolphin’s habitat has been seriously impacted by man-made pollution, such as industry contamination, fishing, and noise. To prevent extinction of the species, conservative action is vital. Prior to any such action, data on the dolphin are essential for decision makers. The current method of observing dolphins is the man-on-boat-watch approach, which is heavily dependent on manpower. Its performance is seriously affected by the weather, fatigue of those on board, and it is also risky and costly. An Internet of things (IoT) data collection mechanism concept is proposed for the purpose of observing dolphins with close watch. It consists of off-the-shelf products such as hydrophones, unmanned aerial vehicles (UAVs) and a specific command and control in search/detection for carrying out the observation task. A Monte Carlo simulation model was developed to analyze the effectiveness of the feasible alternatives, in which some factors are considered and analyzed for their significance. The simulation result showed that the IoT mechanism has an 8.5 times greater chance of availability in operation and at least 2 times more contact than the man-on-boat-watch method. The significant factor affecting the IoT mechanism’s effectiveness is the number of hydrophones and UAVs in the scenario. The great contribution made by this study is that it is the first analytical paper to reveal the effectiveness of an IoT mechanism in benefitting the observation of Chinese white dolphin. The limitation is that it uses off-the shelf products for the IoT mechanism instead of high-end products which could be more effective.