A Web-App for Analysis of Honey Bee Hive Data

The significant drop in honey bee population in recent years has been attributed to Colony Collapse Disorder (CCD). There have been many efforts to monitor honey bee hives and learn about their health and behavior. As part of early efforts for monitoring hives, our research group developed the Beemon system which obtains audio and video recordings as well as humidity and temperature data at beehives for further analysis. In order to make the analysis more efficient and widely accessible, we recently developed a web application to allow easier access to all the Beemon data and provide several tools for analysis. This paper provides details on the design and development of the web application used to make Beemon data available via web-based visualization tools for more effective analysis. Our web application was built using the MEAN (MongoDB, Express, Angular, Node.js) web stack which allowed JavaScript to be used on both the server- and client-sides. This system was built modularly, so the data visualization system was added on as a new server- and client-side module. The system queries data quickly from MongoDB, aggregate views and sends the large blocks of serializable data to the client using Socket.io. The client can interact with our server's data-providing endpoints and flexibly use any client-side data visualization framework. Our system employs C3.js, a D3-based data visualization platform, which includes base charts, to render visualizations of transmitted data.