Mobile networks (3G, 4G or Wi-Fi): they surround us anytime and anywhere, indoors as well as outdoors. Usually, we don’t even realize they are there – unless they’re not working (properly). Without mobile networks, we’re not able to make mobile phone calls, or stream music or video to our smartphones. And in industrial environments, they are crucial as well to ensure companies’ smooth operations (from operating and monitoring machines to sharing information).
However, despite the importance of fully operational (indoor) wireless networks, their planning and roll-out is still largely a manual exercise. Result: in some places in a building there might be no wireless coverage at all, while in other places too many signals are present – resulting in interference. Especially in harsh industrial environments (such as factories and large warehouses), the roll-out of robust and reliable wireless networks is utterly complex and challenging – as signals may get blocked by moving piles of stock and materials, resulting in loss of connectivity.
Solving Wi-Fi coverage and interference issues at ArcelorMittal, Volvo & Egemin
To address this challenge, in 2014, imec kicked off ‘FORWARD’, a project conducted under the umbrella of the imec.icon collaborative research program. It investigated how white spots (i.e. areas that lack wireless coverage) and sources of network interference in (industrial) buildings can be predicted more quickly, using that knowledge to automatically initiate on-the-fly network (re)configurations.
“FORWARD resulted from a very concrete and pressing need down at the production floors and warehouses of imec’s industrial partners ArcelorMittal, Volvo and Egemin,” explains David Plets from imec's WAVES research group at Ghent University. “While their range of activities is very different – from steel and car/truck manufacturing up to the delivery of automated material handling solutions for warehouses and production/distribution centers, each of them was suffering from unstable indoor wireless coverage, massive interference and hand-over issues between Wi-Fi access points.”
The Wi-Fi network that had been installed at the Volvo plant in Belgium’s city of Ghent, for instance, had difficulties adapting to the infrastructural changes that are needed to support the production of new truck models. Moreover, the presence of loads of Bluetooth devices negatively affected Wi-Fi network performance as well.
At ArcelorMittal, steel coils proved to be a major source of wireless network interference. This led to disruptions in the hand-over of the wireless signals that are used to communicate with ArcelorMittal’s moving cranes, resulting in those cranes performing emergency stops.
Lastly, Egemin wanted to investigate how its Wi-Fi network, that is used to communicate with automated guided vehicles (AGVs), can automatically reconfigure itself based on the sudden appearance of big obstacles – so that optimal network coverage (and smooth communication with the AGVs) can be provided at any time.
“Ultimately, FORWARD resulted in a number of approaches to foresee in optimal network coverage, to support a quick hand-over of traffic between (Wi-Fi) access points and to automatically (re)configure those networks on-the-fly – switching access points on/off and adapting their energy levels as is needed,” says David Plets. “Those outcomes, and more specifically the WHIPP tool we developed, now allow us to also help other partners build robust and reliable Wi-Fi networks that continue to operate flawlessly – even in harsh industrial environments.”
WHIPP: accurately predicting Wi-Fi coverage and sources of interference 10x faster
David Plets: “The use-cases at ArcelorMittal, Volvo & Egemin clearly demonstrate that sudden infrastructural changes in industrial plants and warehouses can lead to the creation of white spots. Today, those white spots are calculated through individual, manual access point measurements – a process that takes a lot of time and does not allow for quick network reconfigurations. Hence – in the framework of the FORWARD project – we developed and finetuned WHIPP, a user-friendly software tool that accurately predicts wireless coverage in homes or industrial settings for a given set of access points, based on a simple floor map.”