Almost 23665 swiftlet houses across 63 provinces in Vietnam suffer vast losses of swiftlet nest production due to a lack of monitoring and controlling the suitable environmental parameters in their bird houses. Effectively managing the right factors, such as temperature, humidity, light intensity, sound level, and crowded level, significantly leads to the high production of swiftlet nests. Unfortunately, there are few relevant research in the literature. This research helps to improve economic efficiency in swiftlet nest house farming by applying modern technical methods to monitor essential environmental parameters in the swiftlet house combined with comparative analysis of collected data from real-time continuous sensors. The proposed three-module system can operate on Raspberry Pi, Android mobile applications, and web interface to automatically monitor the swiftlet house and raise warnings for unusual environmental conditions. Our proposed system has been deployed on the authors’ five swiftlet houses that strongly prove the capability and extendability.