![]() ![]() There are also solutions based on dedicated equipment within various indoor locations, which require the deployment of a certain number of special-purpose sensing devices, including cameras, visible light communication systems, RFID, Ultra-Wideband (UWB), infrared, ultrasound, or even laser-based instruments gears. Additionally, positioning accuracy is limited by other factors such as the deployment density of Wi-Fi routers, how often the indoor environment changes, and the effort required to train and calibrate the system. Keeping Wi-Fi signal data up to date can lead to high maintenance costs. However, due to the complexity of indoor environments, Wi-Fi signals are easily affected by interference and can fluctuate widely. These systems can also use signal propagation models and learning algorithms to build a fingerprint map of indoor areas, and then train the system with, let’s say, radio signal strength information for positioning. Different positioning systems rely on signal strength, signal phase, transmission time, RF angle of arrival, channel state information, etc., but in general, they all leverage the differences and correlations between various Wi-Fi signals to determine positioning. Similar to the Bluetooth method, this type of solution determines the approximate position of mobile devices through radio frequency (RF) signal characteristics and triangulation processes. Wi-Fi signals are more commonly found in indoor environments than Bluetooth beacons. However, this solution only works in buildings where iBeacons exist and the limited Bluetooth transmission range results in high costs for deployment and maintenance in large-sized indoor environments (shopping malls and office buildings, for instance).Īnother popular indoor navigation approach is built upon Wi-Fi-based positioning. Based on this information, the app then can calculate a route and navigate the user to her destination. Taking Apple’s iBeacon as an example, a smartphone app can roughly work out the device’s location on a map via signals from one or more iBeacons. So, what are the current applicable ideas for indoor navigation? A relatively well-known navigation approach is based on Bluetooth beacon positioning. Real-time GPS-based indoor navigation is therefore out of the question. Moreover, even with accurate positioning results, map information that most navigation applications depend on is not widely available for indoor scenarios. Signals from a GPS satellite have poor penetration and are often blocked by building walls. Essentially, the receiver chip of the GPS system running on a handheld device picks up positioning signals from satellites and calculates the coordinates of the receiving device. The first step in GPS navigation is positioning. Let’s start by examining why GPS cannot be relied upon for indoor navigation. Indoor Navigation Anywhere: Is It Beyond Reach? Microsoft Path Guide app for Android devices. ![]()
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