Issue link: https://read.uberflip.com/i/1423232
Report Title: Wi-Fi & LoRaWAN ® deployment synergies Issue Date: September 2019 Version: 1.0. final version 32 LoRa Alliance & Wireless Broadband Alliance Confidential & Proprietary Copyright © 2019 Gateways, better 4-5. This is suitable for outdoor places with no / low Wi-Fi coverage. LoRaWAN ® Network is also an enabler for other LoRaWAN ® applications and allows additional use cases. A single IoT device can perform a relatively accurate Wi-Fi based geolocation in indoor and urban areas. The positioning estimation is based on 3D map of Wi-Fi Access-Points. Actual error in positioning depends on density of APs. Normally for an indoor environment it is achieved a median error less than 10m and a correct floor detection >95%. Accuracy is typically <5m with 5 strong Wi-Fi RSSI. Outdoor mobile device with Wi-Fi can be located in urban areas with an average accuracy for around 20 meters. Further improvement can be achieved using Fine Timing Measurements or also called RTT (Round Trip Time) measurements as defined in 802.11mc. If APs and devices have support for this, the error will be in the order of 1m. LoRaWAN ® can provide less accurate network-based location requiring very low battery consumption, in large outdoor areas up to 50m accuracy as demonstrated by KPN in the Netherlands [21]. It is up to the solution provider to develop applications on the edge (e.g. in the IoT device) or in the cloud to opportunistically switch between the two location technologies, or use both to increase reliability, depending on its needs at any given moment in time. Wi-Fi based geolocation is not only very accurate but can be also very conservative in power consumption. Wi-Fi scanning can be done over multiple RF channels and bands. In the urban environment, it is common to see very large number of APs (tens to hundreds). Sending all observed APs to a cloud server can be optimal for positioning accuracy, however it may require sending on the uplink large packets of more than 500 bytes. There are various techniques to reduce Wi-Fi scan payload (down to 12 bytes even) and scan power consumption energy (down to 50mWs) as developed and described by Skyhook in [22]. Demand for location services is extremely elastic and sensitive to price. The total Cost of Ownership of a location service includes the initial hardware investment as well as recurring connectivity and battery charging/replacement costs. The low hardware cost and extreme power efficiency of LoRaWAN ® created a massive disruption of geolocation TCO and made possible many new use cases. Geolocation for campuses, such as large factories and airports, is becoming extremely popular as we can see at Pittsburg international airport rolled-out by Actility [23] and Zaventem airport rolled-out by Proximus Network [24]. The main use cases are as follows: • Reduce search time for lost objects: there are upwards of 5000 moving objects in any large airport; this is also very popular with large parkings of used car dealers, rental companies or car / truck makers. • Verify utilization rate of assets, e.g. on campus car pools. This allows checking whether such pools are oversized or undersized. • Safety badges, tracking location of users in case of emergency evacuations. For countries with nationwide networks, tracking is also popular for many use cases, such as car theft prevention (a booming service in the Netherlands operated by KPN [bike tracking]), child monitoring for outdoor school activities, etc.