What is HiveGuard?

A smart-tech, IoT (”information of things”) based system designed to help beekeepers improve the efficacy of their care through the implementation of sensors, data collection, and an associated smartphone application.

Contextual Inquiry & Cultural Probes

The aim was to gain insights into the daily activities and experiences of beekeepers, particularly focusing on their interactions with bee colonies and hive management. This methodology allowed our team to capture a holistic understanding by exploring the practical, emotional and cultural aspects of their beekeeping practices.

Survey

We recruited participants via r/Beekeeping, contacting local beekeeping groups, and posting on beekeeping Facebook groups. In total, we received 67 survey responses.

Key Findings

1. Parasite and pest management was the most recurring trend in beekeeper concerns.
2. Needs of the hive vary based on the climate and location of the hive.
3. There are polarized opinions on smart tech being feasible in beekeeping.

How might we support and improve beekeepers’ current workflow to ensure optimal health of their bee colonies?

Design Goal

Our goal was to create “smart beehive”, that through data provision and augmentation helps bridge the gaps in expertise for beginner beekeepers and additionally provides actionable information for more advanced beekeepers. We wanted to create a product that helps streamline the hive management process, educates beekeepers, and promotes healthier hives.

Empathy Mapping

We emphasized the recurring trends that emerged during our research phase including identifying and treating pests, finding reliable information regarding hive management, and struggling to effectively respond to hive concerns.

Journey Mapping

We created a journey map of our persona conducting the most common evaluation strategies on a hive: searching for mites, applying mite treatment, checking bee and overall hive status.

Interviews

We interviewed 5 beekeepers. We shared our 6 scenarios with each participant to gain a better understanding on feasibility, acceptability, acceptance, and their overall reaction. Through our interviews, we gained insights into the daily activities and experiences of beekeepers. Further, we were able to learn of primary pain points and supplement the gaps in our knowledge as researchers.

Storyboards of Hypothetical Solutions

User Enactments

Our team conducted two user enactments to better understand the practicality of hypothetical design solutions.

Prototyping Process

Sourcing the beehive

To truly understand how our IoT device would function in a real-world setting, we decided to use a real beehive. This was important because it allowed us to see how the device interacts with a genuine beehive, providing valuable insights into its practical performance.

Building the roof of the hive

Our beehive lacked a cover, so we created one using cardboard. This is where we planned to place our IoT screen and neopixel, as this area sees the least bee activity, reducing the risk of honey accumulation on the hardware. Placing devices within the roof may help cut costs for potential users, allowing them to buy sensors and use our IoT roof system on their existing beehives. Our competitor research showed that other digital beekeeping products are costly, so we considered ways to make our product more financially accessible.

Setting up and coding the TFT

We had started off wanting to use a temperature sensor but we found that it was difficult to set it up, especially with not a lot of support online on how to do this with a particle photon. After speaking to a GSI, we decided to WOz this part of the prototype. We coded the TFT screen to show the hive temperature, when it's too low, when it's heating and when it’s done heating. We also used the workshops to help code the neopixel light which would be used to show that the hive is heating.

Designing the wireframes

In our demonstration, the beekeeper engages with an app. Initially, we crafted a simple user flow to grasp the functionality, followed by designing individual screens. Through multiple iterations, we refined the design, ultimately arriving at polished high-fidelity wireframes.

Prototype Demonstration Key Features

Low-Fidelity Prototype Demo Shots

1. Receive Notification

2. Activate Heater

3. Hive Reaches Ideal Temperature

3. Hive is Updated

Future System Proposal

Current Limitations

Building the temperature function prototype using IoT and Wizard of Oz techniques was a good starting point to illustrate HiveGuard's value. However, it is limited compared to our ideal system proposal, which would balance providing data and information with automating certain beekeeping processes as desired by users. Currently, several factors are limiting us from developing this level of fidelity in the system.

🐝 Feasibility of our primary features needs further research

• Given more time we would have liked to conduct a cost research analysis as well to better understand how much our proposed system would add onto the already considerable financial cost of beekeeping.

🐝 Ideal version

• Because pest management was such a large concern that emerged from our research, we believe that an ideal version of HiveGuard would integrate pest identification and treatment.
• Currently, we do not have the technology to accurately identify, count, and inform a user of the pests within a hive. Products are emerging that attempt to utilize AI to identify varroa mites, but has not been standardized for mass production.

Though we believe HiveGuard would be a useful tool for intermediate beekeepers, we also recognize that beekeeping is not a one-size-fits-all endeavor. Beekeepers have many different strategies for managing their hives, and HiveGuard may not align with all.