Two key problems must be solved in order to electronically score a bull’s performance. First, you must monitor the bull’s motions. Then you have to evaluate the motions and assign a score. You can solve the first problem by mounting the Buckymeter data collection system on the back of the bull (see Figure 1).

In the not so distant past, precision motion sensing was the purview of the military and commercial aviation companies. Picture an inertial navigation system that leads a pilot to his destination half a world away. The more recent explosion in sensing technology for automotive applications (e.g., air bags and stability systems) has led to the development of microelectromechanical systems (MEMS) sensors. These silicon sensors provide sensing technology that rivals the old navigation system in a miniature affordable package.

I used the same sort of technology in the Buckymeter. I simply connected MEMS sensors to a Philips Semiconductors LPC2138 microcontroller. My prototype is based on the Keil MCB2130 evaluation board (see Photo 2). Flash memory chips provide semi-permanent storage of bull ride data. I used soldered and internal memory chips to reduce the overall size of the Buckymeter. I don’t have to worry about losing the chips when they’re subjected to strong jarring forces during a bull ride.

I have wireless access to the data in the Buckymeter. For the prototype, I used IrDA to a Palm Pilot. Depending on your cost and size requirements, RF wireless solutions could replace the infrared link.

To analyze a bull’s performance, you need a good data collection system. You must collect initial sets of data to determine the important parameters and their limits. After you collect data, you must compare the bull’s motions against a known pattern. In order to define known patterns, you must record arbitrary performances. A trained observer can assign scores to various components. The scoring formula then can be applied to future performances to produce a quantitative value for the bull’s performance. Using these methods with existing electronic components and common computing techniques can produce a novel approach to the scoring of PBR bulls.