For user engagement, there are many use cases, but we can mention small use cases or key use cases such as live tracking for users. The most unique part about Juniper Mist User Engagement is not about the use cases because all vendors can offer similar use cases since most are based on integration with third-party developers. All vendors provide an open SDK for any software developer to use this data, but the most unique part about Juniper Mist User Engagement is the accuracy because they have a patent for something called virtual BLE, which enhances the accuracy, allowing us to reach accuracy up to one to three meters for the indoor environment. This is the most unique part about it. Some use cases are embedded in the platform, especially those related to network administrators, such as live tracking for clients, and also some use cases tailored during COVID, for example, to set the capacity for any area, zone, or room and monitor it. If any deviation happens to the zone, it sends an automatic alarm or notification to the admin. This is a sample of what we can achieve using Juniper Mist User Engagement itself. Other use cases related to the end user require an application to be installed on the user equipment, at which point we can provide an open SDK for any software developer to use and utilize the raw data from the system with the same accuracy from one to three meters to be utilized inside their application. By this means, there are endless use cases including indoor navigation, campaigning, advertisement campaigns, and automated attendance. It depends on the developer itself. User engagement with all vendors is based on collecting raw data and conducting extensive machine learning calculations and processing to show it in meaningful dashboards. This is the logic behind the user engagement use case from any vendor perspective. However, to utilize this input, it must be as accurate as possible. The most unique part about Juniper Mist User Engagement is the accuracy because any vendor can collect this data—whether it is Aruba, Cisco, or any other vendor—all can provide this use case. Most of these use cases are based on services from third parties, and vendors offer SDKs that allow developers to tailor their own use cases. But the accuracy of this application depends on the raw data accuracy, which is influenced by the hardware access points. Other vendors such as Cisco and Aruba use triangulation and build their hardware based on omnidirectional antennas, which require many access points to detect the user simultaneously to enhance accuracy. This is why they must add Bluetooth beacons, which are unmanaged devices, leading to management hassles. Juniper Mist User Engagement, however, uses sectorized antennas, eliminating the need for beacon-based devices. Just one access point is sufficient to provide location services, whereas other vendors need at least three devices for detection, achieving around ten meters accuracy. The more devices added, the better the accuracy, but the maximum they reach is five meters. Juniper Mist User Engagement achieves one to three meters accuracy with just a single device without the need for unmanaged equipment. This is the most unique aspect of Juniper Mist User Engagement.
For user engagement, there are many use cases, but we can mention small use cases or key use cases such as live tracking for users. The most unique part about Juniper Mist User Engagement is not about the use cases because all vendors can offer similar use cases since most are based on integration with third-party developers. All vendors provide an open SDK for any software developer to use this data, but the most unique part about Juniper Mist User Engagement is the accuracy because they have a patent for something called virtual BLE, which enhances the accuracy, allowing us to reach accuracy up to one to three meters for the indoor environment. This is the most unique part about it. Some use cases are embedded in the platform, especially those related to network administrators, such as live tracking for clients, and also some use cases tailored during COVID, for example, to set the capacity for any area, zone, or room and monitor it. If any deviation happens to the zone, it sends an automatic alarm or notification to the admin. This is a sample of what we can achieve using Juniper Mist User Engagement itself. Other use cases related to the end user require an application to be installed on the user equipment, at which point we can provide an open SDK for any software developer to use and utilize the raw data from the system with the same accuracy from one to three meters to be utilized inside their application. By this means, there are endless use cases including indoor navigation, campaigning, advertisement campaigns, and automated attendance. It depends on the developer itself. User engagement with all vendors is based on collecting raw data and conducting extensive machine learning calculations and processing to show it in meaningful dashboards. This is the logic behind the user engagement use case from any vendor perspective. However, to utilize this input, it must be as accurate as possible. The most unique part about Juniper Mist User Engagement is the accuracy because any vendor can collect this data—whether it is Aruba, Cisco, or any other vendor—all can provide this use case. Most of these use cases are based on services from third parties, and vendors offer SDKs that allow developers to tailor their own use cases. But the accuracy of this application depends on the raw data accuracy, which is influenced by the hardware access points. Other vendors such as Cisco and Aruba use triangulation and build their hardware based on omnidirectional antennas, which require many access points to detect the user simultaneously to enhance accuracy. This is why they must add Bluetooth beacons, which are unmanaged devices, leading to management hassles. Juniper Mist User Engagement, however, uses sectorized antennas, eliminating the need for beacon-based devices. Just one access point is sufficient to provide location services, whereas other vendors need at least three devices for detection, achieving around ten meters accuracy. The more devices added, the better the accuracy, but the maximum they reach is five meters. Juniper Mist User Engagement achieves one to three meters accuracy with just a single device without the need for unmanaged equipment. This is the most unique aspect of Juniper Mist User Engagement.