The Connected Beehive – An Internet of Things Scenario You Probably Haven’t Thought Of
Unless you are a Southeastern Pennsylvania beekeeper, you probably don’t know that honey bees in this part of the country make most of their honey right now, when the locust and tulip poplar trees are in flower. These large, heavily flowered trees provide a huge flow of nectar that the bees collect, transport back to their hives, dry (with much fluttering of wings), and store as honey. Pounds and pounds of honey. An established hive full of healthy bees can make as much as 30 pounds of honey during the spring honey flow.
As I walked to lunch today in SAP’s headquarters building, I ran into Walt Talunas, an SAP colleague and fellow beekeeper (there are more than a few beekeepers at SAP, including Walt, who is Vice President of the Chester County Beekeepers Association and Keith Jardine, who is the organization’s president). Walt was monitoring the weight of two of his beehives in real-time from his desk. The device that allows him to see that each of his hives has gained around four pounds since 8 a.m. this morning is an Apiara Backyard Hive Monitor. Essentially, his hives, along with hives of many other beekeepers, are connected to the Internet, which transmits data collected from sensors inside or outside the hives to the hive owners and, in some cases, to the public.
Walt’s hive sensors record changes in weight and connect to the internet via his home wifi network (wifi repeater required). Others, like the one in Maryland whose daily progress is charted below, record actual weight (red line) along with internal (black line) and external (blue line) temperatures. Data also collected via wifi.
The short term and long term benefits of this type of monitoring are in keeping with the larger benefits of IoT technology – to enable better decision making by providing access to real-time data from connected “devices” – whether those devices are soda vending machines, tractor engines, home thermostats, electric meters, or beehives.
In the case of an individual beekeeper, hive data recorded every 5-10 minutes a day and collected for analysis can help to:
- Keep hives alive
Healthy hives maintain a steady internal temperature all year round, gain weight during honey flows, and lose weight gradually as the bees eat stored honey over the course of the year. Hives that are losing population due to disease, parasite infestation, swarming, pesticide/herbicide poisoning, or the death of a queen do not have these characteristics. Knowing how each hive is doing every day enables a beekeeper to take action to prevent
loss of a hive by feeding, treating with medicine to counter various parasite/diseases, splitting, combining, moving or otherwise reorganizing the hive.
- Increase honey production
Quick attention to the hive problems listed above can turn a under producing hive into a productive hive and sometimes into several productive hives, all of which increases honey production.
- Improve pollination
Commercial beekeepers make a large part of their income renting their hives to pollinate everything from apples, to almonds, to squash, to cranberries. But a dead hives pollinate nothing. Sensors in hives of migratory beekeepers (even in sentinel hives that might be equipped with a cellular connection to the internet) can help them make better decisions about when to move hives from one farm field to another and could even, with the appropriate sensors, enable them to tell if/when their bees have been exposed to agricultural chemicals.
- Improve breeding stock
When a hive starts to gain weight in the morning is an indication of how early the bees fly out to collect nectar and pollen. How much weight a hive gains is an indication of size and vigor of the colony. Beekeepers can improve breeding decisions with access to this data and raise queens from better stock, promoting an improved genome.
In the case of the larger agricultural and scientific community, data collected from bee hives all over the US could help researchers correlate colony health with external data such as weather, cropping patterns, sales and applications of agricultural chemicals, and other factors under consideration as causes of colony collapse disorder. Add in genomic data and you have a huge body of data whose analysis stands a chance of improving honey bee survival.
Software companies are often accused of promoting solutions in search of a problem. What beekeepers and agribusiness have here is a problem in search of a big data/IoT solution. As an SAP beekeeper, I would be so happy if SAP’s IoT Cloud Platform could contribute to the solution.