Providers of Public Wi-Fi can maximise its value when it is provided in places that they may naturally congregate. Subsequently, finding where people congregate with a Wi-Fi enabled device is important for deciding upon the location of Public Wi-Fi Access Points. This article describes our method in detail on how these locations may be determined, based around the wardriving method.
Firstly, an explanation. Wardriving is an approach for collecting information about Wi-Fi Access Points in a particular area. Information about a particular Access Point can be collected using a Wi-Fi transceiver and some software. The amount of information you can collect is determined by the type of antenna you have and its sensitivity, the type of transceiver you use (some collect and make visible more Access Point data than others), and the software you are using to interpret this data.
Planning. We typically run a wardriving study of a particular area in a car, mounting a high gain Wi-Fi antenna on the roof and driving a pre-planned circuit of the area. To get an accurate picture of the topology of Wi-Fi enabled devices in an area, we will collect data in the circuit during sessions when there is likely to be high and low traffic. In addition, we also wardrive the circuit a few times each session to determine the natural stickiness of people (do they stay in the same area, or are they simply moving through).
Setup. Our normal setup for conducting a wardriving study includes:
- High gain Wi-Fi antenna that can be roof mounted,
- GPS receiver that can also be roof mounted. We use a BU-353-S4 USB GPS Receiver,
- Specialist Wi-Fi transceiver. We use a Netsys transceiver like these and as needed by our wardriving software. List of supported Wi-Fi cards can be found here,
- Laptop – any one with two USB ports (for Wi-Fi transceiver and GPS receiver), and
- Wardriving software – We use Acrylic Wi-Fi Professional.
Crunching the data. We typically extract Access Point data from Acrylic Wi-Fi in KML format and plot this data either using Google Maps or in an open source GIS application like QGIS. What we are looking for, in the first instance, is the density of Wi-Fi enabled devices and Access Points in a particular area and this done by manually reviewing the data. What we do next depends upon our design objectives. If the objective is to implement a community mesh network, we would look for areas where areas of higher Wi-Fi device and Access Point density overlap. If, for example, a local government authority is looking to supplement backhaul into a community mesh network, then we would look to find an overlap of higher WI-Fi device and Access Point density, and these are in close proximity to Council owned infrastructure (where it is likely council access points and backhaul could be provided at lower cost than if these Access Points were installed on infrastructure not owned by Council).
Good Public Wi-Fi solutions are clear in their objectives and are designed with these objectives in mind. Good Public Wi-Fi design relies on understanding your current environment and your target audience in detail. Wardriving is one method that can provide a wealth of data for informing this design. But at the end of the day, this data is only useful if interpreted from the perspective of your objectives.
Finding the best channel for a Wi-Fi access point, by Bill Hess at Pixel Privacy – https://pixelprivacy.com/resources/best-wi-fi-channel/