In this insight, we discuss how companies such as Aerial Technologies, Mist Systems, Mojo Networks and Quantenna Communications are adding intelligence to W-Fi hardware and software to drive improvements in customer experience.
The challenges of Wi-Fi network performance
Although the availability of in-building cellular connectivity is improving, Wi-Fi is the most common way of distributing broadband internet access within homes and office. It’s not only smartphones, routers, tablets and laptops that are Wi-Fi connectable. Today, Wi-Fi’s ubiquity makes it a popular choice for consumer electronics and smart home and home appliance vendors to make their devices more interactive and remotely programmable.
But Wi-Fi is not without its challenges. Adding more and more devices to a network can strain capacity and lead to performance issues. Signal strength in parts of the home distant from the router can be weak, causing buffering when streaming video or causing printers to go off-line just when you need to print out an important document.
Managing the performance of Wi-Fi networks can be challenging for professional IT services teams, which must deal with spikes in usage and new devices and people coming on to the network, and even more difficult for the non-technical home user. This can lead to frustration, particularly for the home user, and adversely affect their satisfaction levels with the ISP or telecoms operator providing broadband service. For the ISP or telecoms operators, customer concerns and complaints over quality of broadband can lead to higher costs in the form of increased customer service calls and engineer visits or lost revenue in the form of churn.
Using AI to improve network performance
The concept of self-managing telecoms networks, using analytics, has been around for a several years. More recently, several vendors have developed solutions that use artificial intelligence (AI) techniques to manage and improve Wi-Fi performance. Among these are Mist Systems and Mojo Systems.
Mist Systems was formed in 2014, is based in Cupertino, California, and counts Lightspeed Venture Partners, Norwest Venture Partners, GV (formerly Google Ventures) and Cisco Investments among its leading investors. Mist Systems core solutions combine hardware (access points) and software (Mist Cloud). All access points are enabled with 802.11ac Wave 2, a dynamic vBLE 16 antenna array to enable location services, additional radio to collect data and adminster rules set in the Mist Cloud and an expansion port to enable other forms of wireless IoT connectivity. The Mist Cloud ingests data from access points and applies machine learning algorithms to monitor network trends, send alerts to technicians when service levels fall below defined thresholds and makes recommendations on proactive configuration changes. Among Mist Systems’ clients and partners are Delta Airlines and IKEA.
Mojo Networks was founded in 2003 and is headquartered in Mountain View, California. In February 2017 the company completed a combination of Series E funding and debt of $30 million. Among investors in this or previous funding rounds were Alpha Technologies, Granite Ventures, Morgan Stanley Private Credit & Equity, Presidio Partners,Trident Capital and Walden Riverwood Ventures. The core components of its offering are access points, Cognitive Cloud Wi-Fi, Layer 2 switches and a multiservice platform that enables enterprises to migrate controller-based WLAN deployments to the Mojo cloud environment. Mojo Networks access points integrate 802.11b/g/n and 802.11a/n/ac radios and Gigabit Ethernet ports: different models are targetted at specific uses cases such as enterprises, stadiums or guest services. Cognitive Cloud Wi-Fi integrates a cognition plane that applies machine learning to the data gathered from access points to predict and address performance and security issues. Mojo has worked with Reliance Jio, the major Indian operator, in the deployment of a nationwide public Wi-Fi network.
Leveraging Wi-Fi to create new revenue opportunities
Ensuring consistent Wi-Fi quality of serive is critical for enterprise and home users alike. But enhancements to Wi-Fi infrastructure, using AI, also represent an opportunity to generate new revenues. A recently announced partnership between Quantenna Communications and Aerial Technologies is a good example of this.
Quantenna Communications was founded in 2006 and is based in San Jose, California. It is a provider of chipsets (including 802.11ax) and software for a range of Wi-Fi products such as access points, gateways, repeaters, routers and set-top boxes. Its target customer segments are service provider, retail, wireless ISP and enterprise.
Aerial Technologies is a developer of software solutions that applies machine learning techniques to existing Wi-Fi infrastructure to enable motion detection services. Its target customers include ISPs and MSOs, healthcare players, security systems integrators, and smart object manufacturers.
Under the partnership, Aerial Technologies’ AI motion recognition technology will be integrated imto Quantenna’s Wi-Fi chipsets. The companies are jointly working with leading ISPs to offer Aerial's motion detection and motion recognition services to their customers. Among the commercial services that ISPs can offer using this solution are intrusion detection, elderly monitoring, and home automation.
IHS Markit forecasts that global shipment of WLAN access points will rise from 29.6 million in 2018 million to over 42 million in 2022. Over the same period, the shipments of 802.11-based ICs used for devices across a range of applications will rise from 3.2 billion to around 4 billion.
The growing scale of devices, from consumer to enterprise and industrial, connecting to WLAN access points means that the task of managing Wi-Fi networks and ensuring sufficient quality of service is becoming more challenging. The wealth of data that can be gleaned from Wi-Fi networks represents an opportunity to address such challenges. Analytics performed on this data may identify the relationship between, for instance, particular types or patterns of traffic and service degradation. Beyond this, AI and machine learning bring the capability to predict and mitigate performance issues. As such, AI capabilities will increasingly be baked into Wi-Fi hardware and its accompanying management software.
As the initiatives of Quantenna Communications and Aerial Technologies indicate, there will also be efforts to extend the native capabilities of Wi-Fi technologies to offer new services, such as context-aware motion detection, which can be used to monitor the elderly at home or the presence of unwanted intrusion. This type of innovation will be critical in ongoing effort to enrich the telco smart home offering and boost ARPU beyond traditional services such as voice, broadband and video.