The global indoor positioning and indoor navigation (IPIN) has witnessed gradual acceptance among industry segments over the past few years. Industry verticals such as healthcare facilities, transportation hubs, huge recreational and retail spaces, and educational campuses among others have begun adopting indoor location technology to aid in optimal facility management through strategic decisions based on real-time data.
Indoor Positioning – Market Statistics
According to leading research firm Markets and Markets, the global forecast for indoor location technology which accounted for USD 5.2 billion in 2016 will grow at a Compound Annual Growth Rate (CAGR) by 42% and reach USD 40.99 billion by 2022.
Another research firm Stratistics MR has forecasted that the indoor location market will grow at a CAGR of 35.9%, reaching USD 29.4 billion by 2022.
Though there is a significant difference in the numbers predicted by both these agencies, there will nevertheless be a growth of at least 37-38% by 2022 from where the market stands today.
In addition to the indoor location market, the global micro-location market is expected to grow at a steady pace as well registering a CAGR of 19.4% to reach almost USD 34.1 billion by 2024 – based on a study conducted by Markets And Markets.
Indoor Positioning – Challenges
As has been pointed out in an in-depth study in the context of a cultural heritage site such as a museum, accuracy, availability, and stability are the most common challenges which IPIN technology needs to address.
In addition to these the challenges, cost of procurement, installation, and maintenance seems to be a concern with the facility management of a campus.
Another recent research paper also presents challenges that crop up due to different devices using Wi-Fi for indoor localization. After testing heterogeneous devices in both laboratory and real conditions to analyze their performance, authors Machaj, Brida and Majer have presented their findings, detailing the parameters which can have a negative impact on the functionality of a positioning system.
Artificial Intelligence for Indoor Positioning Systems?
Held in Nantes, France, the 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN) witnessed researchers from the field presenting their work over a four day period.
While the best paper award went to Niitsoo et al. for their work on convolutional neural networks for positioning estimation, Gkoufas & Katrinis representing IBM research presented an AI-centric indoor positioning system, naming it Copernicus.
Gkoufas & Katrinis propose that Copernicus is a self-learning adaptive system with improved accuracy across Smartphone models. They say, “Copernicus leverages a minimal deployment of Bluetooth Low Energy (BLE) Beacons to infer the trips of users, learn and eventually build tailored Magnetic Maps for every smartphone model for the specific indoor area.”
As can be gathered from the contents of this, indoor positioning technologies are set to gain a better standing in applicability and consumption while adapting to new technological advancements, resulting in optimal facility management from a 360 degree perspective.