# SpaceSheep: Satellite Communications for Ovine Smart Grazing
###### Abstract  
The application of IoT-based methods to support pastoralism allows the smart optimization of livestock operations and improves the efficiency of the activity. The use of autonomous animal control mechanisms frees the shepherd to carry out other tasks. However, human intervention is still needed in cases such as system failure, the bad or unpredicted behavior of the animals, or even in cases of danger, the welfare of the animal. This study documents the enhancement of an alarm generation system, initially developed within the scope of the SheepIT project, to monitor animal behavior and equipment, which warns the human operator of the occurrence of undesirable events that require intervention. Special attention was given to the use of case scenarios in places without Internet access, such as rural areas. Therefore, the system was integrated with a satellite interface, as a way of guaranteeing the timely delivery of the alarm messages. To ensure an acceptable operating cost, the system was further optimized in terms of message encoding, considering the cost of this type of communication. This study assessed the overall performance of the system, evaluated its scalability, and compared the efficiency gains from the optimization, as well as the performance of the satellite link. a 2023 10, 340. [[https://doi.org/10.3390/vetsci1005034010](https://doi.org/10.3390/vetsci1005034010)]([https://doi.org/10.3390/vetsci1005034010](https://doi.org/10.3390/vetsci1005034010))  
During vineyard grazing, animals are continuously tempted by vine leaves and their fruit. The collar detects the movement of the animals biting the leaves and compares the height of the neck during this process. As soon as the biting movement is detected above the maximum height threshold, the collar begins the conditioning process [3] through the emission of sound and electrostatic stimuli. Once the posture is reversed, the collar cancels the stimulation mechanism. Furthermore, so that the animals can rest at their normal size, only the biting movement triggers the execution of the posture control mechanism. Animal behavior [6], over time, evidences the continuous attempts of the animal to violate the maximum height, while the collar avoids the animal attacks on the vine leaves and grapes. Although it has been developed as an automated conditioning mechanism, the system still requires human supervision and maintenance to ensure animal and crop safety. System failures, a lack of maintenance, and animal well-being require human supervisors to monitor animal behavior offline and intervene. SheepII field-trial tests [6] demonstrated the importance of automating the shepherd's job, as labor costs were reduced by freeing the shepherd to perform other tasks in the vineyard. In addition, the use of animal monitoring tools allows the identification and prediction of a wide range of animal-related events [6; 7; 8; 9]. In [6], [PERSON] et al. monitored the behavior of animals that were freely grazing throughout the day. It was verified that the ingestive behavior predominantly occurred at the beginning of the day, followed by a more static behavior in the afternoon, which was probably related to the digestion period. Using the same animal monitoring infrastructure, [PERSON] et al. [9] located the animals in a free grazing environment, having tracked the movement of the animals over a period. The results demonstrated the possibility of performing animal localization using a low-cost localization mechanism, although a localization error that depends on the location of the transmitter beacons was also found. The same monitoring infrastructure was used again, this time to create a dataset after monitoring goat kidding [7], as well as the nocturnal activity of sheep [10]. The analysis of the animals' nocturnal activity data allowed [PERSON] et al. [8] to verify the existence of a set of rest and activity cycles during the night, as previously reported in the literature.