Currently, the presence and levels of air pollution in most stingless bee farms are not measured periodically nor there are proper monitoring levels that can be attributed to hive productivity. Long-term measurement and monitoring of air pollution for hive productivity and honey yield have not been performed. Therefore, this research proposes long-term and real-time air pollution measurement and monitoring techniques that are important for correlation analysis and parameter modeling. By using air pollution detection sensors through a wireless sensor network topology in stingless bee farms, details of pollutant presence and levels will be available in real-time over a long period of time for hive productivity correlation analysis. With such deployment using IoT -based systems, data can be easily accessed from anywhere thus ensuring data continuity. This paper describes a preliminary study on the design, development, and testing of real-time air pollution measurement and monitoring systems capable of determining the health status of stingless bee nests in mixed livestock crop farms. The goal of this research is to help beekeepers/users maintain control and be able to take quick action on the hive from the information obtained.
