# A Low-Cost IoT-Based System to Monitor the Location of a Whole Herd
## 4 Discussion  
The system described in the present paper has been designed to be a low-cost and practical solution for commercial farms. The cost of the GPS collar, which is in the range of 100-150 \(\upupup\) per device, is lower than that of similar solutions [32; 33; 34] and the cost of the BLE tag is at least ten times lower than the cost of the collar. Thus, depending on the collar/tag ratio, the cost per animal can be very low compared to existing solutions. For example, in the case of 10 collars every 25 tags, which was found to be an adequate ratio to have daily data of all sheep in the herd, the cost per animal is 36-54 \(\upupup\). This figure translates into 18-21 \(\upupup\) per sheep per year considering a device lifespan of five years, service cost included (battery change and connectivity). On the other hand, the weight of the GPS-based system (265 g) can be considered low for more than 365 days of operational life, which is longer than that of other low-cost system described in scientific literature [33; 35]. In [36] a lighter GPS device to be placed on an ear tag is described, but it has an operational life of a few weeks. In the case of BLE tags, total weight is only 25 g for an average operational life of 280 days. Another important feature for commercial applications is device robustness. The collars were all retrieved with no damage and could be redeployed in other farms. In this regard, several existing solutions place the GPS antenna on the top of the collar [37; 38] or into a shoulder-mounted harness [22], because an antenna is most accurate and most efficient when it is pointed towards the sky with nothing obscuring its view [39]. This was considered inadequate for the present solution in terms of robustness and manufacturing cost. As BLE tags do not provide GPS coordinates, the accuracy of location data gathered from tags is lower than that of collars. Information about the power of the advertisement message is used to compute a radius around the collar position inside which the tag is located. It can be sufficient for most applications in commercial farms and even for some research studies. The GPS/Sigfox devices used in this work recorded a location fix for 60% (sheep farm) and 66% (beef cattle farm) of all attempts. These results are in the range of those reported by [33] on wild others using a low-cost GPS/GPRS telemetry system, or by [40] on bison and caribou. Using a store-on-board GPS collar, [38] reported a GPS fix-success rate of 99%, but the terrain was flat and there was no dense tree canopy. Several authors have reported that habitat characteristics, such as topography and tree canopy, may significantly reduce location acquisition [41; 42]. Nonetheless, GPS error is a systematic error, which can be computed with many methods or mitigated by some augmented methods, such as ground enhancement signal networks or satellite enhancement networks [43]. In this experiment, although \"dehesas\" can have a dense tree canopy, most missing location fixes were not due  
Figure 7: Hourly evolution of the percentage of collar messages with (green) and without (grey) tag data (25 collars and 25 tags): (**a**) sheep farm; and (**b**) beef cattle farm. to GPS failures, but to the lack of Sigfox coverage. Despite this, it is important to highlight that signal penetration is better for Sigfox than GSM [44]. On the other hand, regardless of the differences in Sigfox coverage between farms, a tendency has been observed for cow collars to gather more location fixes than sheep collars (unpublished data). It is probably due to the higher position of the GPS antenna when placed on the neck of a cow. Some authors have previously used short-range communications for tracking animals. Most of the reviewed solutions used passive radio frequency identification (RFID) tags together with antennas placed in strategic points of the building where the animals are housed. Different solutions have been developed and tested, e.g., for laboratory animals [45] or for zoos [46].