**4.5. Geo-fencing and virtual perimeter**

Geo-fencing, virtual perimeter or geo-zoning simply means creating a virtual barrier or perimeter around a geographical area of interest [42, 43]. It has also been defined as an enclosure, or a boundary without the use of physical barriers. It can be accomplished by using a combination of RFID, LoRaWAN and GPS based location sensors for instance. Sensors obtain the location of the subject of interest relative to a map. Geo-fencing has been used in numerous fields such as fleet management and logistics – to monitor movement of vehicles, proximity marketing – which prompt users of products when they are close enough, asset management – which send alerts when an asset is moved without authorization, people monitoring – such as in monitoring movement of children and employees and in law enforcement – to restrict and/or monitor persons of interest.

**Figure 8.** Aerial mustering using a UAV.

**Figure 9.** A virtual fence around a grazing area.

Geo-fencing has also seen immense application in Agriculture, more specifically in free-range livestock farming. Sensors are placed on collars of cattle, goats etc. and these send location data to the farmer. There are two major forms of application of geo-fencing in agriculture: in the first, the sensors simply notify the farm owner when animals have grazed outside a predefined perimeter [44]. In this system, the farmer has to actively go muster the animals back into the perimeter. In the second approach, the animals are given subtle stimulations when they wonder outside set perimeter. Such simulations might include high frequency sounds or low voltage jolts – this approach depends on associative learning [45]. An illustration of a geo (virtual)-fence is shown in **Figure 9**, with the red boundary showing the grazing area and the blue circle showing an animal grazing outside the boundary.

Recent research work has focused on improving the efficiency of geo-fencing technologies. Low cost GPS being the most commonly used geo-fencing sensors have an error range of between 5 and 10 m and sometimes take long to locate and lock on to the required number of satellites. In a bid to improve on them, Assisted-GPS and WiFi have been used to respectively improve accuracies and reduce the time-to-first-fix [43]. LoRaWAN has recently been introduced as an alternative protocol for accurate location of animals [44, 46].

Though some arguments have been raised with respect to the effectiveness of geo-fencing, such as in the work of [47], rather than purely depending on stimuli, UAVs can be used to steer the animals back into range when they roam out of grazing perimeters. UAVs can therefore provide a cheap and effective way of getting animals back "inline" and are particularly useful when a number of animals stray outside different ends of the perimeter.
