Broadcom Corporation has announced the industry’s first 5G Wi-Fi (802.11ac) system-on-chip (SoC) to deliver pinpoint indoor positioning technology. The BCM43462 SoC, featuring Broadcom’s new AccuLocate technology, provides sub-meter accuracy on physical locations enabling retailers and public venue operators to deliver more personalized experiences to consumers.
Analysts predict the indoor location market to reach $4 billion in 2018, fueled by increasing demand for location-based services in public venues such as shopping malls, department stores, airports and stadiums. By leveraging location-based services, retailers and venue operators can offer discounts, promotions and personalized services to consumers based on exact locations while enterprise network IT staff can use the technology to track and manage assets, Broadcom said.
Broadcom’s latest 5G Wi-Fi SoC with on-chip AccuLocate technology operates using fine timing measurement (FTM) technology, resulting in highly accurate positioning regardless of environmental factors, Broadcom said. Previous versions of indoor positioning relied on received signal strength indicator (RSSI) technology, where signal strength and performance can vary depending on environmental factors such as crowd density or temperature.
“Broadcom’s latest 5G Wi-Fi innovation with integrated AccuLocate technology delivers highly accurate sub-meter pinpoint technology that rivals the capabilities of outdoor location based technology,” said Ed Redmond, Broadcom vice president and general manager, Compute and Connectivity. “In addition to providing a more customized user experience, this technology has the added benefit of allowing venue operators to monetize their investment in existing Wi-Fi infrastructure.”
“Location-based technology installations will break the 25,000 mark in 2014, while mobile devices capable of supporting indoor location will reach hundreds of millions within two years,” said Patrick Connolly, ABI Research senior analyst. “Rising demand for these services by the world’s leading venue operators and retailers is generating an immense opportunity for leading component suppliers, such as Broadcom, who are early to market with innovative solutions.”
About 5G Wi-Fi
Increased reliance on wireless networks, the explosion of video consumption and growing number of wireless devices are all putting tremendous stress on legacy 802.11a/b/g/n networks. With new innovations that allow for more reliable coverage, 5G Wi-Fi technology addresses these challenges, allowing mobile device users to stream digital content between devices faster, and simultaneously connect more wireless devices to home and enterprise networks, while conserving battery power.
Key Features of the Broadcom BCM43462 SoC
Dual-band (2.4 GHz and 5 GHz) complete 5G WiFi (11ac) SoC with integrated MAC, PHY and radio
Three-stream spatial multiplexing up to 1.3 Gbps
State-of-the-art security provided by industry standardized system support
Embedded hardware acceleration enables increased system performance
Full IEEE 802.11a/b/g/n legacy compatibility with enhanced performance
Support for FASTPATH® UAP, Broadcom’s enterprise class access point software
Availability
Broadcom’s BCM43462 SoC with integrated AccuLocate technology is now sampling. AccuLocate technology is also available on Broadcom’s BCM43520 5G Wi-Fi 2X2 SoC, BCM43460 5G Wi-Fi 3X3 SoC and BCM4354 5G Wi-Fi 2×2 MIMO Combo Chip.
When one talks about the worldwide location industry, mobile resource management — fleets and trucks, for instance — aren’t sexy at all, but they make money. What is supposed to be sexy is location-based advertising. According to many analysts, location-based advertising has been hampered by a few things: education for both consumers and mobile advertisers, privacy issues, and relevant proximity information so folks can use it to make purchases. Another concern could be the expense of rolling out indoor beacons.
BARCELONA—Major consumer privacy concerns aside, companies are starting to see growth in location-based advertising, with new markets emerging in Europe. While the numbers of mobile advertising companies has decreased at the Mobile World Congress, held here in February, from just two years ago, the remaining players are seeing a more mature market.
Mobile advertisers are beginning to realize that location is the Holy Grail for growth, said Cameron Peeples, Airpush vice president of marketing. “People going into New York from Newark during rush hour can receive a different call to action because of a created geo-fence. Advertisers can determine whether the traveler is there on business or looking for a hotel and other travel deals,” he said.
Before Mobile World Congress, Los Angeles-based Airpush partnered with AirX, a large mobile ad exchange company. The majority of the AirX inventory, about 120,000 Android applications, includes highly-sought-after GPS location data, the company said.
There are large differences between the North American and European markets for mobile advertising, Peeples said. “The mobile advertising market [in Europe] is definitely evolving. The European market is key for us, dramatically higher than other markets,” he said. “[The European] market seems to have people connected to a lot of things — they are more mobile, use public transportation more, and always have a phone that is more centric to who they are.”
Making location-based advertising relevant to the consumer is still a major challenge. “Our focus next year is on native advertising. Native advertising combines not only the right message, but the right delivery vehicle,” Peeples said. “No one bicycling enthusiast wants ads tailored for someone who wants flowers.”
Peeples said the privacy issues are a big deal, but his company’s services are opt-in. “A lot of it is loyalty advertising. It’s all opt-in,” he said.
xAd Partners with Waze, Sees UK Growth
Another mobile advertising company, New York-based xAd, is also making inroads in Europe. “We are in the UK right now, which is really WiFi-focused. A lot of our early [location-based] advertising efforts are in education — to educate consumers and the advertising agencies about the power of location and mobile,” said Monica Ho, xAd vice president of marketing. “Not all location is created equal. The real value of [location-based advertising] is the proximity target to market to.”
Right before Mobile World Congress, Waze selected xAd as its third-party provider of search and display mobile ads in the United States. Waze, which was bought by Google in a deal worth more than $1 billion, is a top three map and navigation app in the iTunes store — a ranking that was probably helped by the Apple Maps debacle in 2012.
The companies say the deal will place xAd’s mobile ad targeting technologies into Waze’s location-based advertising platform.
Ho said there are still two areas of concern for location-based advertising: relevancy to the consumer and privacy issues. “There was privacy backlash from Nordstrom collecting consumer information from their Wi-Fi system,” she said, referring to the controversy last year when the retailer was accused of capturing consumer information during an indoor positioning test.
Apple to Roll out Upgraded Maps on iPhone 6
Speaking about Apple Maps, many industry analysts says the company has come a long way since the very public embarrassment nearly two years ago over map inaccuracies and flaws. The company recently released iOS 7.1, but is expected to rollout iOS 8 when the iPhone 6 debuts later this year.
With the debut of the iPhone 6, an updated version of Apple Maps will also be released, according to published reports.
Last year, Apple bought two companies, HopStop and Locationary, to allow the company to entrench itself once more in the location business. How firmly those roots prove to be, and how well they serve the company against archrival Google, remain to be seen.
Apple has been stockpiling companies and mapping software since its introduction of Apple Maps on iOS devices, which had a rough start. GPS World’s LBS Insiderreported extensively on the problems Apple encountered with its mapping software. Some of these problems included sending drivers to a wrong location and direction.
After the mapping software problems were made public, Apple CEO Tim Cook apologized for the mapping software’s problems and even suggested that users go to such competitors as Waze, MapQuest, and Microsoft’s Bing.
In other location news:
A Wall Street Journal reporter basically said there was nothing much new at Mobile World Congress — and that the excitement and action was at the outlying conferences at Fira Montjuic. One of these more interesting conferences, Four Years From Now, or 4YFN, featured start-up companies making pitches and displaying their new products, some of which included location capability.
The Mobile World Congress final stats. Organizers said MWC had more than 85,000 attendees from 200 countries — an increase of 13,000 from the previous year. It’s now being touted as the biggest and best wireless show.
In February, GPS World reported that TruePosition had purchased Skyhook for an undisclosed price. Skyhook provided location services to a number of companies including Apple and Samsung. The interesting issue is Skyhook’s lawsuit with Google, which alleged that the Internet giant influenced smartphone manufacturers to abandon the Boston-based company. According to published reports, the legal action still is going forward.
AT&T Mobility is shuttering its location-based Alerts marketing program. The company said it would release an updated version later this year. AT&T Mobility launched Alerts in late 2012. It featured free opt-in, location-based text message alert service. Participating retailers included Stapes, Gap, Zales, Neiman Marcus, and others.
I didn’t go to South by Southwest. Is my cool-guy card revoked? One of the reasons I didn’t is because, outside of meetings that were not part of the conference, there was not one location industry announcement made there. Maybe something will change my mind next year, but call me an old fogey — I just didn’t see the need to go to Austin this year.
Google’s 3D mapping project, Project Tango, is putting prototypes into developers’ hands.
Google has been collaborating with universities, research labs, and industrial partners in nine countries, to concentrate the past 10 years of research in robotics and computer vision into a mobile phone. “We now have prototypes ready to put into the hands of eager development partners that can help us imagine the possibilities and to transform those ideas into reality,” Google said on its Project Tango website.
Google’s Advanced Technology and Projects group (ATAP) heads the project, which aims to make it possible to create a 3D model of the space around a smartphone. For instance, a user can map an area, such as a home, by walking around with the phone.
Creation of 3D maps in this way would make it easy to navigate through buildings such as offices and supermarkets. Maps of a user’s home could also be used in games. As Google said on its website, “Imagine playing hide-and-seek in your house with your favorite game character, or transforming the hallways into a tree-lined path. Imagine competing against a friend for control over territories in your home with your own miniature army, or hiding secret virtual treasures in physical places around the world.”
The current prototype is a 5-inch Android phone containing highly customized hardware and software designed to track the full 3D motion of the device as a user holds it, while simultaneously creating a map of the environment. These sensors allow the phone to make more than a quarter million 3D measurements every second, updating its position and orientation in real time, combining that data into a single 3D model of the space. The mapped space is matched to the phone’s internal gyroscopic systems and more general location data from GPS.
TomTom has begun a strategic partnership with indoor-mapping company Micello Inc., extending its range of mapping products to include indoor venues.
Integrating Micello’s maps and venue content gives TomTom’s business customers access to accurate pedestrian friendly indoor maps with points of interest data in venues worldwide.
“The indoor mapping functionality means that step-by-step guidance can be integrated into daily life for a wide variety of venues, including shopping malls, airports and retail stores,” said Charles Cautley, managing director, TomTom Maps. “By partnering with Micello our customers can now develop smarter apps and locations-based services helping users navigate with ease in and out of the car.”
“We’re excited to be partnering with TomTom, the global leader in navigation.” added Ankit Agarwal, CEO of Micello. “Our agreement means that TomTom’s business customers can use our indoor venue maps and incorporate the content into their automotive, online, or mobile solutions.”
The Mobile World Congress in Barcelona has turned into a mini Consumer Electronics Show. The term “Internet of Things” is the new hot buzz word this year. The show had an estimated 75,000 attendees spread across two sites and eight football-field-sized exhibit halls. While the connected car continued to have high visibility, other technology such as location-enabled advertising and indoor positioning received buzz.
BARCELONA — Fueled by connected car popularity, automakers and vendors converged on the Mobile World Congress here to assess the market in a continent that has not fared well economically. Some say the European market for location products is slower than that of North America — others say it is doing fine.
In this climate, a few automobile analysts have indicated they were worried that a large player such as Google or Apple will swoop in and take control of the connected car market — and tell automakers what to put in a vehicle. Last month, Google even formed its own group, the Open Automobile Alliance, with GM, Honda, Audi, Hyundai and chipmaker Nvidia.
Jorg Brakensiek, Car Connectivity Consortium chair of technical work group and Nokia principal architect, smart devices, doesn’t believe that Google will tell automakers what to do when it comes to connected vehicles. “Android is a consumer electronic device. Completely different than what we do,” he said. “Certainly, there are complimentary applications. We are not dominated by a single partner.”
At MWC, the Car Connectivity Consortium, or CCC, rolled out MirrorLink Developer Fast Track to allow developers to gain MirrorLink certification, an industry standard for car-smartphone interoperability, for their connected car applications. “We believe in standardization of the technology. But also do not put restrictions on business models and feel we allow a very open ecosystem [for members],” Brakensiek said.
Several industry analysts have said that the connected car market will eventually drive the autonomous vehicle movement, also championed by Google. Brakensiek said people still have to make the decisions — driverless cars initially will not be fully autonomous. “People have to make the judgment whether to hit the kid, or drive into a car next to them. Will that decision be made entirely by a car? I hope not,” he said.
CCC said that Coyote, Glympse and Parkopedia are the first developers admitted to the program. CCC said developers will have access to technical support, social media and press inclusion, promotion of the application among members and other benefits.
At an MWC developer’s conference, CCC said that Peugeot Citroen will roll out two MirrorLink-enabled vehicles, the C1 and 108, at the Geneva International Motor Show.
One company, Cincinnati-based RacoWireless, has been working with a number of overseas wireless carriers as well as automakers to power connected vehicles. The company recently signed a deal with AT&T Mobility to connect the Audi A3 line to LTE. As GPS World reported, AT&T had announced its LTE commitment to Audi at CES.
“We want to have our customers get the connectivity they need. We have signed dozens of carriers [worldwide], but now we are looking at more strategic partnerships,” said John Horn, RacoWireless president, who also says the Latin America is a growing market, working with its carrier partner, Telefonica, there.
At MWC, RacoWireless said it would integrate Inmarsat’s M2M service into its Omega Management Suite. The OMS is a cloud-based dashboard that helps to enable RacoWireless’ network of more than 1,000 providers. The deal could be significant as satellite connectivity services, required in remote areas, are growing in the M2M market.
Magellan Boss Outlines Strategic Vision
One of the companies trying to establish deep roots in the connected vehicle market is Magellan. Peggy Fong, Magellan president, said the company’s strategic focus is now in two areas: Wearables and connected vehicles.
“We have set a clear direction for the company in next few years. Our focus will be the cloud connected car, which is not traditional navigation,” she said. “Our other focus will be wearables. We saw that market coming when we identified that [portable navigation device] sales were declining five years ago.”
Magellan’s first foray into the wearable/smartwatch market wasn’t a success. The new product, Echo, was launched at CES, works with a smartphone. “The first product built a foundation. We are focusing on the sports watch market, which is different than the fitness market,” Fong said.
In addition to Magellan’s rollout, Garmin teamed up with Sony at MWC to offer navigation on a smartwatch. The app has speed warnings, traffic tracking, social media capability. The unit, launching later this spring, has a monthly service charge.
Fong believes that navigation on a watch won’t catch on because consumers are already carrying a smartphone with that capability. “We don’t believe navigation is the best use for a watch,” said Fong, who indicated that the company was working on other applications for its own wearable product.
Garmin also is offered its Navigon, Streetpilot navigation units for iPhones, iPad, Android and Windows phones at MWC. Its Head-Up Display Plus was getting a lot of buzz at the Showstoppers event the day before the conference.
Established Location Companies Exhibit at MWC
Telecommunication Systems’ two location entities — one based in California and the other in Washington state — displayed location-based services and navigation systems at MWC.
TCS rolled out its DopplerNav embedded weather overlays at the show. The company is also trying to establish a foothold with European wireless carriers with its Gokivo 2.0 location-based technologies for both Android and iPhone smartphones.
“Users can see real-time weather and be able to adjust routes around it. The released version of the product is scheduled for April, but we are rolling it out in Europe,” said Michael Loo, TCS senior marketing manager, of the new DopplerNav unit.
The company’s Seattle unit, which was made up of former Autodesk employees, is seeing inroads in Latin American markets. Europe, however, has been a tough nut to crack as carriers haven’t signed up for its white label locater product.
“Our Family Locater and Workforce Locator products are doing well in Latin America. We are trying to gain a foothold here in Europe,” said Javier Ferraez, TCS senior product manager, location applications.
Overall, TCS was one of the companies that had been hurt by Google’s free maps and navigation, but is now seeing growth in niche LBS and navigation areas.
Also at MWC, Nokia’s Here unit had a few product announcements such as a mapping product with CNN; Here maps and turn-by-turn navigation integration into the parent company’s first Android-based phone, Nokia X (which doesn’t incorporate Google maps and navigation); Here Auto Cloud that powers Volvo navigation; and even location-based games.
Where’s Indoor Positioning?
Some of the usual industry players had displays on indoor positioning, but there were no big announcements. Such companies as SK Telecom displayed beacons with centimeter-level accuracy that leverage Bluetooth, Wi-Fi and UWB technology.
“We have indoor and outdoor beacons. The outdoor beacons can last three years without a battery change,” said John Kwon, Idolink CEO, who was displaying a system that is not on the market to assess European carriers’ interest.
SK Telecom displayed its augmented reality platform, also not yet on the market, which allows users to point a camera at an object, have it identified, mapped/located and described. The company says it will allow the development of many business-to-business and business-to-consumer augmented reality services and content by third-party developers. This may open the door to several markets such as advertising agencies, education and publishing companies.
In other Mobile World Congress news:
ALK Technologies showed off its free CoPilot GPS app, which has turn-by-turn navigation. The app has a new feature called CommuteMe, which learns a driver’s daily commute routing, tracking streets and freeways they frequently use. ALK was another company that focused on enterprise markets, particularly when Google invaded the market with free maps and navigation.
Is the Mobile World Congress outgrowing Barcelona? Seems as if it is almost as hard to get a hotel room, flight and other travel as it is to the Consumer Electronics Show in Las Vegas. One attendee said he found great lodging near the conference, but obtained it in October. Others in the industry believed that the enormous trade show is getting too expensive — and too far away — to realistically attend and market products and services.
There were many more meeting rooms this year than at previous MWCs. Many companies are opting in on these private venues to talk with customers and potential customers.
Mark Zuckerberg came out in his trademark short sleeved T-shirt and jeans. He promoted Internet.org, an effort to get the web into underdeveloped countries. Of course, he was talking to a room of wireless executives and others who would have to build/pay for that capability. He also said he was done acquiring companies for now — does that mean there will be no $19 billion Whatsapp pay day for a location company?
WASHINGTON, D.C. – The Federal Communications Commission today proposed rules to help emergency responders better locate wireless callers to 911. The proposed updates to the FCC’s Enhanced 911 (E911) rules respond to Americans’ increasing use of wireless phones to call 911, especially from indoors, and take advantage of technological developments that allow for more accurate location information to be transmitted with 911 calls.
The FCC’s current E911 rules require wireless providers to automatically transmit information to 911 call centers on the location of wireless 911 callers within certain parameters for accuracy. These rules, which were adopted in 1996 and underwent their last major revision in 2010, enable wireless providers to meet this accuracy standard based solely on the performance of outdoor wireless 911 calls.
However, many Americans are replacing landlines with wireless phones, and calling patterns are changing. For example, reports indicate that nearly 73 percent of 911 calls in California are made from wireless phones, and approximately 80 percent of all smartphone use occurs indoors.
In light of these trends, the FCC today proposed changes to its E911 rules to include indoor location accuracy — particularly location accuracy in challenging indoor environments such as large multi-story buildings, where first responders are often unable to determine the floor or even the building where the 911 call originated. Determining the location of indoor wireless callers is more challenging than determining an outdoor location, but innovation and technological developments in this area are making it easier to locate mobile devices wherever they are, the FCC said.
The FCC proposes in the near term that wireless providers meet interim location accuracy metrics that would be sufficient to identify the building for most indoor calls. The FCC also proposes that wireless providers deliver vertical location information that would enable first responders to identify the floor level for most calls from multi-story buildings.
In the long term, the FCC seeks to develop more granular indoor location accuracy standards that would require identification of the specific room, office, or apartment where a wireless 911 call is made, according to the statement by the FCC. These standards would rely on the advancing capabilities of indoor location technology and increasing deployment of in-building communications infrastructure.
The FCC also proposed additional steps to strengthen its existing E911 rules to ensure delivery of more timely, accurate, and actionable location information for all wireless 911 calls. In addition, the FCC is seeking comment on whether to revisit its timeframe for replacing its current handset- and network-based location accuracy standards with a single standard in light of technological developments.
While seeking comment on its proposals, the FCC also encouraged industry, the public safety community, and other stakeholders to work collaboratively to develop alternate proposals for its consideration. The FCC emphasized that its ultimate objective is that all Americans – whether they are calling from urban or rural areas, from indoors or outdoors – receive the support they need in times of emergency.
As smartphones embrace always-on, ubiquitous location, location-based sensor fusion will become a standard feature. ABI Research’s report, “Location-based Sensor Fusion: Companies, Technologies, and Revenue Opportunities,” outlines how sensor fusion will evolve to support indoor location and the companies best placed to succeed in this space. Location-based sensor fusion will enable the dawn of the quantified self, ambient intelligence, as well as provide huge potential around advertising and retail, ABI Research said.
Senior analyst Patrick Connolly comments, “Sensor fusion is vital in enabling a consistent location experience, RF mapping, and the industry to scale rapidly. Unfortunately, it is not just a case of putting in a 9-axis sensor to achieve this. Highly complex algorithms are required to optimize sensor outputs, integrate with other location technologies and combine with machine learning and data-fusion algorithms. Sensor fusion will surpass Wi-Fi and BLE as the most important handset-based indoor location technology by 2017.”
ABI Research has forecast the adoption of different indoor location technologies, and the companies best placed to be successful. “We see a significant trend towards hybridization, with Wi-Fi, BLE, and senor fusion proving to be vital. By 2014, hybrid solutions will have already surpassed standalone indoor location technologies on smartphones. Longer term, technologies around optical light, object recognition, and LTE-direct are all forecast to offer differentiation,” continues Patrick Connolly.
VP and practice director Dominique Bonte adds, “The market is largely divided between Sensor IC OEMs, GPS/connectivity IC OEMs, and a group of really interesting start-ups. Companies like Movea, HillCrest, indoo.rs, and Senionlab are creating some intriguing solutions and will represent the next generation of acquisitions and partnerships in indoor location.”
These findings are part of ABI Research’s Location Devices Research Service, which includes Research Analyses, Market Data, Insights, Presentations, and Competitive Assessments focused on the indoor location market.
Sonata is a self-service advertising platform for the retail world.
Currently, 96 percent of world trade takes place through traditional brick and mortar stores. Add almost 1,000 million smartphones with integrated GPS to that retailing picture and a whole range of advertising opportunities, with high added value for advertisers and consumers, opens up. Sonata was begun l to drive foot traffic to local retailers’ point of sale via potential customers’ smartphones.
Sonata divides the world into 90-square-metre plots. The plots are uploaded with local business adverts, which then appear on smartphones and tablets that come in range of the advertiser according to the smartphone’s geolocation. Sonata has been developed by TAPTAP Networks, a Spanish mobile advertising market leader based in Madrid.
The process of uploading an advertising campaign is very simple for the retailer and takes no more than three minutes, according to Sonata. A retailer doesn’t need a website or even a mobile app; all that’s required is a minimum investment of £50. Advertisers follow three steps:
registration using an email address;
adding the store details (just one or a whole network);
choosing the ad’s geographical area and the design of the ad from one of Sonata’s creative templates (or advertisers can create their own design).
“Any local business, including those without technical know-how, can create an advertising campaign,” says Alvaro del Castillo, CEO of TAPTAP Networks and the developers of Sonata.
“An added attraction of Sonata is that local businesses only pay for actual results-calls, registrations, clicks, purchases in the store… whatever form of contact a customer makes-and can choose how much to pay for them,” says del Castillo.
“The Sonata platform is focused on meeting the need of the local small-business sector, which views the online world as a major threat with the ever-growing pressure it exerts from ‘showrooming’ and the selling of cost price goods by major e-commerce players,” explained de Castillo.
On October 2, NextNav announced that Broadcom Corporation acquired a commercial license to NextNav’s Metropolitan Beacon System (MBS) technology, a so-called terrestrial constellation that brings GNSS-like performance to indoor and urban environments where satellite-based positioning is either unavailable or significantly degraded.
The agreement enables Broadcom to integrate NextNav’s location technology into its mass-market GNSS connectivity and mobility platforms, used primarily in cell phones and tablets.
NextNav President and Founder Ganesh Pattabiraman characterized the deal in a conversation with GPS World: “This is a commercial license to a Tier 1 chipset provider, whose products are in a vast number of smart and feature phones in the country. The partnership enables our technology in a low-cost, high-volume form factor. This is important for us since we don’t make chips. We rely on partners such as Broadcom. This is the first of many such agreements; we’ll have more through the year.”
Most wireless companies have a mobility group addressing cellular modems, the central clearinghouse for so-called connectivity: the combination of Wi-Fi, Bluetooth, GNSS, and other technologies. Standard assisted GNSS (A-GNSS) packages to date in such cases generally consist of ephemeris from all GNSS satellite constellations supported by the wireless company’s chips, cell ID and Wi-Fi ID from base-station databases, and additional proprietary assistance mechanisms.
The NextNav MBS concept shares many operating principles with GNSS satellite constellations, but because the NextNav beacons are installed terrestrially instead of in space, they transmit sufficient signal strength for reliable reception indoors and in urban canyons where a clear view of the sky is unavailable. MBS is deployed much like a cellular network, to provide consistent indoor positioning to every building within a covered metropolitan area. MBS offers both accurate horizontal positioning and highly accurate altitude information, a particularly important capability for emergency responders in urban and indoor areas where GNSS systems tend to be most challenged.
NextNav built its MBS network across forty large U.S. markets (see list at end of story) with its own Federal Communications Commission (FCC) licensed spectrum. “We bring more a managed network providing consistency and reliability of position information,” continued Pattabiraman. “Also the vertical component that other systems do not provide.” He characterized Wi-Fi, for example, as “an unmanaged network,” subject to frequent changes without a centralized and continually updated source of certified data.
NextNav location performance was recently highlighted in side-by-side technology tests conducted by the Communications Security, Reliability, and Interoperability Council (CSRIC) of the FCC, and published in March of this year; see reportage and analysis of these tests at The Inner Edge: Who Holds the Key to Indoor Nav?
The trial compared the performance of location systems across urban, suburban, and rural areas in the San Francisco Bay Area for determining the location of callers during emergency calls (E911), a critical case for mobile-phone users. NextNav was the only technology capable of reporting a valid height or altitude estimate, enabling floor-level positioning. NextNav’s horizontal accuracy results also reduced first-responder “search rings” by 90 percent over its nearest competitor.
Don Fuchs, director of business development at Broadcom, added “Nextnav is a metropolitan area location system, which is typically a wider area than that covered by Wi-Fi. Wireless emergency assistance calling (E911) needs a wider venue covered. And across 40 metro areas. Nextnav is wide area, while Wi-Fi is essentially local area.”
Pattabiraman said that in a typical metro area, NextNav’s terrestrial constellation of beacons is deployed for maximum coverage and minimum GDOP, and is not constrained by capacity like a cellular network. He stated that the San Francisco Bay area covered by NextNav extends to 900 square miles, from South San Jose into Marin County and East Bay. “With a fraction of the beacons required for cellular coverage in the same area, which would be in the neighborhood of a few thousand antenna installations, our deploy and operating costs are much less. Less than 20 percent of that for a cellular network.”
In comparison with Locata, another recently rolled out terrestrial constellation designed to fill GNSS gaps, Pattabiraman said, “Locata and NextNav are two entirely different systems serving different needs. We are in the mass-market commercial cell phone wide area use case, filing that gap, providing 5–10 meter accuracy, with vertical as a critical component, and full market coverage.Locata covers centimeter-level precision application in localized environments. The two companies could both eventually get to the other side [of the market-sector spectrum], but currently each of us is focused on the particular requirements of our designated market areas.Also, we operate with licensed spectrum versus the Locata operation in 2.4 GHz unlicensed.”
“At the highest level, they are both multi-lateration systems. Time of arrival, time difference of arrival. We arrive at our core synchronization via GPS, which has its own synchronization, but we’ve got our IP on top of that to improve it. Each beacon is autonomous. You can drop it anywhere with a clear view of the sky, and it is synchronized to the rest of the network, it has its own self-synchronizing mechanisms. Locata is a synchronized network.
“Another way of looking at it, they have a replacement for GPS. We do more complementing for GPS, we count on GPS being there.”
Broadcom’s Fuchs added, “From the perspective of a company designing GPS and GNSS client-side semiconductors, we view NextNav as a terrestrial constellation, no more difficult or challenging than adding support for any new or legacy constellation like BeiDou or GLONASS. We see this integration as being very straightforward, we have lots of IP in the area of signal processing, these sort of signals, this sort of positioning algorithm. We add NextNav as a secondary technology for challenging urban conditions. We view this as a piece of location technology to develop and integrate as the market demands.
“In six years at Broadcom and seven before that at Global Locate (acquired by Broadcom in 2007), we have a history of turning support like this, we’ve been able to do this very quickly. Depending on market demand, in less than a year. I can’t lay out a roadmap at this point. We expect to see market demand for this, certainly expect regulatory demand. We wanted to get to the point where we can react to that in less than a year. That was the motivation to get this agreement into place, and we are now positioned.”
“We all operate under standard operating environments as specified by the FCC. We’re metro-wide just like paging towers or broadcast TV,” continued Pattabiraman. “We’re not necessarily doing anything different as regards the indoor environment. We’re not adding anything additional to the noise spectrum or floors. Our maximum transmission is 30 watts, very small compared to cell transmission in kilowatts. It is bits per second by the time it hits the receiver. Because it’s calibration for navigation, the network design is optimized for location. We take into account GDOP and coverage, maximizing the latter, minimize the former. There is a very low throughput. It’s a tradeoff between power and coding. We code the heck out of this thing. We just new a few bits to get our information through, not like cellular that needs to get megabits through.”
As to any data or issues about the human health impacts of an RF-rich indoor environment, Pattabiraman concluded, “There’s none of this concern about power into your head. We transmit only at the tower, receive only at the user. It is very, very heavily coded, like GPS, and very low-powered. It’s not even close [to cell transmission power]. We’re a feather, they’re a hammer.”
List of NextNav Covered Metro Areas
NextNav characterizes San Francisco as built to “commercial grade” and the other markets as “Initial Builds.”
Boston-Worcester-Lawrence, ME
Syracuse, NY-PA
New York-North New Jersey, NY-NJ
Philadelphia-Wilmington-Atlantic City, PA-NJ-DE-MD
According to a new report by Research and Markets, the winners in making and operating mobile phones will offer the most compelling new functionality, IPS being a major enabler. The winners in making, integrating and operating RTLS will reduce cost and improve usefulness, not least to encompass mobile phones and other mobile computing. The world’s largest companies are locking horns on this.
The term Indoor Positioning Systems (IPS) primarily concerns location-based services on mobile phones where GPS does not work. The term Real Time Locating Systems (RTLS) primarily concerns locating people and things at a distance, securely, using second generation RFID. The subjects are converging with Apple, Samsung, Google, Nokia, Microsoft, Hewlett Packard and IBM clashing for the tens of billions of dollars of business that is emerging.
This subject heavily involves short range communications, notably Wi-Fi and Bluetooth, and inertial navigation and advanced RFID as it progresses to determining 3D position including orientation and line of travel. Emergency services, healthcare, retailing, manufacturing, logistics and many other industries will be transformed by what is becoming possible, Research and Markets said.
The topics of IPS and RTLS embrace a value chain from research and consultancy to software, services, hardware, integration and facilities management. Mobile phone app developers and value added enhancements plus ecosystems of mobile phones, web services and more are also involved.
Most of the development and use is in the USA, but other territories are racing to catch up. For example, the new Indoor Location Alliance came from Europe but has global players and companies, such as Samsung in East Asia, and is taking an exceptionally broad view from new phone design to RTLS in smart cities. Siemens in Europe and several Japanese and U.S. companies seamlessly integrate GPS outdoor navigation and services with IPS and RTLS.
This report consists entirely of evidence-based analysis following seven years of conferences, masterclasses and reports on the subject produced by the PhD level IDTechEx analysts and team.
The main features of the report, which is continuously updated, are the following:
Ten year forecast of the RTLS market 2014-2024, platform hardware vs system integration/services.
Full explanation of what IPS and RTLS are and how these technologies are evolving and converging, with detailed, original graphs and diagrams, largest orders landed and lessons arising. Threats, opportunities and company strategies are revealed.
Comparison of 105 organisations in the IPS/ RTLS value chain by country, basic measuring principle, standards, frequencies, protocol, range, accuracy, applications targeted and background information. Pie charts and graphs give analysis by parameter.
Comparison of 74 case studies of RTLS with many pie charts presenting the lessons arising.
Detailed original interviews carried out from mid 2013 with important organisations in this space.
Glossary of the challenging jargon, which is different between IPS and RTLS yet often refers to the same or similar things.
If we wish to obtain consistently usable positions indoors using a mobile phone, we can augment its GPS or GNSS receiver with other unfettered sensing technologies such as gyroscopes and accelerometers supplemented by radio signals of opportunity. But is all of this actually feasible? The authors have conducted tests of a multi-system approach to positioning indoors with favorable results.
INNOVATION INSIGHTS by Richard Langley
IS GPS REALY A GLOBAL POSITIONING SYSTEM? Well, that depends on your definition of “global.” If it means that GPS operates well all over the world in environments where it was designed to work, then, yes, it is a global system. But, if you define global as meaning that GPS operates well everywhere not only outdoors with a clear view of the sky but also indoors and in other restricted environments, then (as some have argued), GPS is not truly global.
So why doesn’t GPS work (for the most part) indoors? Our mobile phones do and they use similar bits of the electromagnetic spectrum. The basic problem is that the signals from GPS (and other GNSS) satellites are just too weak to easily penetrate buildings. They are more than strong enough to yield excellent positioning, navigation, and timing (or PNT) results if the antenna connected to the receiver can “see” the satellites unobstructed. But even outdoors, trees, buildings, and mountains can block the signals from one or more satellites at a time. And indoors, the signals are usually attenuated by walls, floors, and ceilings so much that a conventional receiver cannot lock onto them.
Receiver manufacturers have developed more sensitive receivers that can operate, at least to some degree, indoors but with a good antenna. And receiver chips or modules with this more sensitive technology are often found in modern mobile phones. But they don’t typically provide reliable indoor positioning because they are being used with inexpensive, suboptimal antennas. Some potential improvement in indoor positioning capability is possible by supplying the receiver with satellite orbit and clock information through the mobile network rather than having the receiver acquire this information directly from the satellite signals. This assisted-GNSS technique allows a receiver to work with weaker signals. But it is not a panacea. Gaps or holes still exist for positioning indoors or in other obstructed environments, prompting one industry wag to liken GNSS coverage to Swiss cheese.
So, what are we to do if we wish to obtain consistently usable positions indoors using a mobile phone? As we will see in this month’s column, we can augment or bypass its GPS or GNSS receiver with other unfettered sensing technologies such as gyroscopes and accelerometers. These devices can be made very small using microelectromechanical technology and are already included in some mobile phones.
However, there are some issues with these devices for positioning, not the least of which is rapid position drift. We can restrain the drift by using magnetometers, for example – also present in some mobile phones. We can also use radio signals of opportunity to help in the positioning – signals available in the phone such as multi-generation mobile signals, Bluetooth, and Wi-Fi through their signal strength “fingerprints.” But is all of this actually feasible?
The authors of the article in this month’s column have conducted tests of such a multi-system approach to positioning indoors with quite favorable results. Are we at the stage of accurate positioning (and tracking) everywhere? Not quite, but we are getting closer.
“Innovation” is a regular feature that discusses advances in GPS technology and its applications as well as the fundamentals of GPS positioning. The column is coordinated by Richard Langley of the Department of Geodesy and Geomatics Engineering, University of New Brunswick. He welcomes comments and topic ideas.
In recent years, there has been increasing interest in ubiquitous positioning — accurate location fixes in any environment, outdoors and indoors. We have all become used to the availability and performance of global navigation satellite systems (GNSS) for accurate outdoor radio positioning with a reasonable degree of reliability and availability. However, indoor radio positioning is more challenging because GNSS signals do not penetrate buildings well, and we must instead rely on local infrastructure and other available inputs to aid the user.
Indoor radio positioning is, however, available to the general public today through the use of signal strength fingerprint databases managed and provided by third-party providers such as Skyhook. These typically use Wi-Fi and cellular signals because of their ubiquity and the prevalence of appropriate receiver circuits in consumer devices. The user can also access the fingerprint database through these media. These systems, therefore, have two clear constraints: the database must have been previously built via some form of survey process, and the user must have a data connection available to obtain it. A more scalable system would not rely on such constraints, and would instead develop its own database during operation.
The benefits of such a system are significant: it can provide location-based services, situational awareness, and asset tracking in new and unknown environments for consumers, emergency services, the military, lone workers, security personnel, and autonomous vehicles. There is no requirement for a data link to function, nor any prior surveying of the radio environment, nor any other prior knowledge such as a floor plan or map. However, the system can also be used to quickly and easily generate maps of the radio environment or floor plans, which can be beneficial for organizations wishing to provide positioning services to the public using a simpler positioning method; that is, this method can be used to rapidly survey an area and generate a signal fingerprint database for other users to exploit. Best of all, all of this can be achieved today in real time using an app for a consumer smartphone.
The Digital Swiss Army Knife
The last couple of decades have seen steady improvements in a variety of sectors that have led to new and flexible navigation capabilities — and all of these improvements can now be found in the little chunks of silicon, plastic, and glass in our pockets and handbags. Moore’s Law and the miniaturization of electronics have enabled us all to carry handheld programmable supercomputers around with us every day. Microelectromechanical systems technologies and the demand for better gaming and augmented reality experiences on our smartphones mean that any new phone contains the same types of sensors for enhancing user experiences that cruise missiles and smartbombs use to ensure they hit their targets precisely.
Finally, your smartphone contains more radios than you probably realize. GPS (or GNSS); 2G, 3G, and 4G network radios; near field communications, like RFID; Bluetooth; Wi-Fi; and even a VHF FM chip might be tucked away in there somewhere. The near future is likely to bring a “whitespace” radio (using re-assigned vacated spectrum) along with a 60-GHz wireless USB transceiver. We are bathed in a phenomenal number of radio signals as we go about our daily lives, completely oblivious to the rich tapestry we are walking through — an invisible, permanent, detailed map just waiting to be sensed by our smartphones and annotated for our navigation purposes.
So, just what is possible with a commodity smartphone and its arsenal of features?
Pedestrian Motion Modeling
We can begin with the accelerometers, magnetometers, gyroscopes and barometers found in recent smartphones. These sensors collectively form an inertial measurement unit (IMU) that can be used to track the motion of a user through any environment, regardless of the availability of GNSS (at least in theory).
Unfortunately, there are many stumbling blocks in the way for any new navigator starting down this road. The standard approach for inertial navigation involves using the gyroscopes to maintain an estimate of the orientation of the device relative to the Earth, and to integrate the accelerometer measurements to calculate the system velocity and subsequently the change in position with each measurement update. A key aspect of this process is the removal of the effect of gravity, which requires us to estimate the value of the local gravity field strength (which varies with location across the globe) and its direction (which we do based on the estimated orientation of the device according to the gyroscopes). There are inevitably some errors associated with the estimates of both of these quantities.
In addition, the sensors themselves suffer noise, biases, instabilities, non-linearities, and other effects that only decrease the system performance further. These errors accumulate over time because the position and orientation estimates at any moment depend on the cumulative sum of all measurements since the start of the journey. The result is rapid and unbounded growth in position and orientation error. The cost of the sensors is, of course, tightly correlated with their quality, and so the rate at which the navigation performance degrades. The quality of the sensors in smartphones is so low that this approach is rendered useless within the first few seconds of use. To make progress we must apply regular position corrections to the system by applying external constraints or incorporating external sensor measurements.
Alternative. GNSS measurements provide constraints and corrections for inertial navigation systems, but here we are considering operating indoors where these are unavailable or severely degraded. An alternative solution for most smartphone users is to use the inertial sensors in a different manner, within a so-called pedestrian dead- reckoning (PDR) approach. Here, it is assumed that the device being tracked is held by (or attached to) someone walking in a manner that can be modeled. The inertial sensors are not now used to reproduce the full 3D motion of the device at the update rate of the sensors, but instead used simply to detect stepping motions and to infer that the user has moved some number of steps. Looking for patterns in the accelerometer data where minimum and maximum thresholds are exceeded within a certain time window is a surprisingly robust step counter when the user walks “normally” (more complicated actions such as side steps and stumbles require more complex algorithms). The smartphone can estimate its orientation by fusing together its gyroscope (which offers good short-term orientation-tracking) and its magnetic compass (good long-term orientation-tracking with periodic fluctuations from local magnetic anomalies). The step length of the user (a surprisingly consistent quantity) and any bias in the gyro-smoothed compass heading can both be measured and modeled during periods of GNSS availability such that the best possible estimates are available when GNSS is lost.
FIGURE 1 shows the functional flow diagrams for a strapdown inertial navigation system (top) and a PDR system (bottom). Note that the PDR scheme accumulates error more slowly than the INS scheme (involves fewer integrations over lower-rate data) but is heavily dependent on the performance of the gait recognition, floor-change detection, and step-length-estimation algorithms.
FIGURE 1. Functional flow diagrams for a strapdown inertial navigation system (top) and a pedestrian dead-reckoning system (bottom).
However, PDR techniques still accumulate error, resulting in gradual position drift, but with much higher performance than would be achieved by integrating the raw data in the traditional INS manner. Typical PDR schemes can track the user with an accuracy of a few percent of the distance walked, although this performance degrades with any un-modeled motions that confuse the step detector, such as infrequent backward or sidesteps. So how do we deal with this issue?
Machine Learning
The accuracy of PDR schemes is dependent on the validity of the pedestrian motion model. Any un-modeled action has the potential to generate false positive events in the step detector and hence contribute to position error. Users may stoop, crawl, jump, hop, or shake their device while static — motions that are all very difficult to unambiguously discriminate in raw sensor data.
There are many approaches to solving this problem of gait recognition, and most exploit machine learning techniques. The basic principle of supervised machine learning is that a large set of labeled training data (that is, lots of manually categorized data of each type) is analyzed by a computer in order to extract patterns, statistics, or certain measurement sequences from the inertial sensor measurements that reveal the type of step that was taken. In unsupervised learning, the clusters and categories within the data must be found by the algorithms themselves.
The outputs from such algorithms are typically thresholds, signatures, and other learned metrics that can be installed in a smartphone and used to dynamically classify movements. It is also possible to deploy the learning algorithms on the device itself so that it can learn what the particular user’s signatures are to permit better step and gait detection (like training a speech-recognition program to understand your accent). A simple example of this is running an error-state Kalman filter while GNSS signals are available to determine the user step length and to detect any background compass bias that is corrupting the system.
A problem yet to be resolved for PDR schemes is a basic physical one: the laws of physics are the same for an object at rest as for one moving at constant speed. This means that it is theoretically possible for a suitably skilled person to simulate the “already moving at constant velocity” version of any of these motions while static by moving the device in just the right manner, effectively spoofing as many steps or motions as they like. The opening and closing phases of a journey (that is, the very first and last steps) are critical in distinguishing real and spoofed motion if only inertial sensing is used to disambiguate real and spoofed motion through an environment. We will, however, return to this problem in a moment.
Simultaneous Localization and Mapping
The application of machine learning can be extended to the entire indoor navigation problem using a technique called Simultaneous Localization and Mapping (SLAM). A key aspect here is the hypothesis that there are some measurements that can be taken within an indoor environment that vary rapidly on the spatial scale but only slowly on a temporal scale. These opportunistic measurements are typically of radio signal strength (Wi-Fi, cellular, television, VHF FM, and so on) and magnetic field strength, although in principle many other metrics could be used such as light level and temperature. They are deemed to be opportunistic because they already exist in the environment and have not been generated specifically for this positioning system. Moving along a corridor is expected to result in a particular sequence of measurements that is repeatable on the next visit to that corridor with a confidence based on the time since the last visit. Tight agreement is expected within the next few minutes, close agreement within the next few days, and so on. It is not expected that these fingerprints will necessarily be valid for months or years, as objects may move around the environment; for example, large items may be relocated and Wi-Fi access points may be moved. The ability to exploit the expectation of high repeatability over short time periods of a few hours is the key to developing a system that can learn about its environment and improve its performance during use.
As the device moves through the indoor environment (with position estimate driven by the PDR estimation), the opportunistic fingerprints are captured and stored. If the device returns to a region it has been in before, then it will record a sequence of measurements that will agree closely with the previous sequence that was recorded in the past. This provides a constraint to the system: whatever path was taken in between, it has converged with a section of its historical path and “closed a loop.” Any offset in these two path sections at this point reveals the inertial error that has accumulated during this loop. The system can therefore correct its own inertial error growth, allowing extended operations in GNSS-denied areas.
Fingerprint Maps. The gathered opportunistic measurements can also be used to generate fingerprint maps of the areas that can be shared with other users to allow them to accurately position themselves within those areas in the future, reducing everyone’s reliance on PDR schemes and removing the need for environments to be manually surveyed for their environmental maps. The maps are automatically calibrated and corrected by the SLAM process. As more users operate in the environment and more data accumulate it is easier to identify and remove erroneous data that does not fit into the consensus being formed by the “intelligence of crowds.” This opportunistic navigation scheme can also feed back into the PDR scheme to aid with motion detection — as fingerprints are expected to vary on a fine spatial scale as users move through an environment. They can be used to detect when a PDR device is in reality static, but being moved in a manner that is erroneously triggering the step-detection routine.
FIGURE 2 shows a plot of the magnetic-field-strength variations recorded during four walks down the same corridor of a building at four different times of day on four different days. The traces have been manually aligned by the clear drop in field strength at step number 40. A fixed step length was assumed, and the relative stretching evident across the traces is due to small differences in walking speeds across the tests. Step-length changes can be estimated using changes in the stepping frequency, and the typical step length can be observed and calibrated during periods of GNSS availability.
FIGURE 2. Repeatability tests of the magnetic field strength from four walks along an indoor corridor at four different times during the day on four different days.
There are two distinct classes of SLAM algorithm for PDR. The most common class involves an iterative batch process applied after the data have been collected (that is, offline). This process (which might be least-squares fitting or maximum likelihood estimation, for example) identify loop closure points and provide an optimal joint estimation of the path taken by the user that satisfies these constraints and the raw odometry data as much as possible. The
Wi-Fi SLAM approaches, Gaussian Processes Latent Variables and GraphSLAM, both use such schemes. The results are typically robust, but the offline processing stage can be lengthy.
SLAM can, however, be performed in real time, even on a smartphone, by exploiting an efficient multi-hypothesis scheme. As the user moves, we retain multiple hypotheses for their position and, crucially, record the history of each hypothesis. This is typically done using a particle filter, where each particle represents a unique hypothesis. In this context, we must store the tree of ancestors for each particle at each epoch. When we detect a loop closure, we prune the history to remove all hypotheses that did not result in a loop closure at that point and therefore dynamically correct our errors. Note that each particle can even be assigned different parameter values, such as step length or heading bias, and if a gait detection scheme cannot confidently identify the type of step taken, new particles representing every possible user motion at that epoch can be generated.
Occupancy Grid. Rather than running a specific loop closure algorithm, an occupancy grid is used, whereby the environment is defined by a grid of small cells, for example, one meter by one meter squares. As each particle propagates, representing a hypothesis of the user path, it posts its identity and the current step number into the occupancy grid. As the user continues to move, the particles check the grid cells they move through for any previous visits. If a particle has visited a cell before, the current sensor measurements are compared to those recorded at the time of the last visit. If there is close agreement (typically scored using metrics such as the Euclidean or Mahalanobis distances) then that particular particle is given a high weight. Conversely, poor agreement results in a low weighting.
The entire particle cloud can be reweighted accordingly with low-scoring particles being killed and high-scoring particles being duplicated. The result is the particle cloud collapsing towards the region of close agreement between old and new sensor measurements. Because the occupancy grid contains the historical path of each particle stored via their IDs and step-number sequence, when a reweighting of particles occurs, the historical path of the user is updated and improved accordingly along with the current estimate of the user’s location.
The SLAM estimate can be improved by many types of observations, not just loop closures. If the user moves outside and confident GNSS locations become available, these can also be used to reweight the particle cloud. If the user moves into a region where the floor plan of the building is available to the positioning engine, particles can be pruned whenever they try to cross walls. If desired, even direct user interaction such as manually tapping the map on the smartphone display could be used to provide a position estimate and so constrain the particle cloud.
FIGURE 3 shows six stages from a walk around the corridors of a building using an indoor positioning smartphone app to track the user. The red dashed line shows the trace using just the PDR scheme, which exhibits gradual degradation in positioning accuracy. The green solid line shows the trace using SLAM to constrain the PDR error growth using magnetic anomalies and Wi-Fi signal strengths.
A further modern advance is in computer vision: the use of cameras and algorithms to monitor and interpret features in the environment. The movement of features within the field of view from frame to frame can be used to determine the motion of the camera if it is assumed that the majority of the objects tracked through the view are actually static in the environment. Consistency checks between features allow those corresponding to other moving objects to be filtered out.
The result of this visual odometry scheme is the ability to determine the speed and heading changes of the camera by observing the optical flow of the environment. As with PDR approaches, integrating over visual odometry measurements results in motion tracking with much slower reduction in accuracy over time and distance than for systems built upon traditional IMU integration (accelerometers and gyroscopes) alone. If specific objects or features can be uniquely identified and recognized when seen again in the future, then SLAM techniques can also be applied. At the moment, smartphones are powerful enough to apply computer vision techniques and calculations at moderate update rates of a few frames per second. As smartphones become more powerful, or if mobile operating systems will, in future, permit these computer vision algorithms to be deployed on the dedicated graphical processing units, or even perhaps if devices such as Google Glass result in the deployment of dedicated computer vision chips within devices, we will see computer vision coupled with augmented reality move to the forefront of smartphone navigation.
The Future
Our desire for accurate positioning and tracking anywhere will never go away. The availability of cheap, accurate GPS over the last decade has resulted in accurate positioning, navigation, and timing not only being something we take for granted, but something society has come to depend upon. The positioning capabilities of our smartphones will continue to improve, not only because of the new developments and capabilities described above, but because of new infrastructure developments.
The In-Location Alliance is a large consortium of companies including big names like Nokia and CSR who are defining standards for Bluetooth and other beacon-based positioning technologies for dedicated deployments in indoor environments such as shopping centers, airports, and museums. The new 4G LTE signal structure also contains a dedicated ranging signal to permit traditional timing-based positioning schemes to be easily deployed using these new cellular standards. All infrastructure-based schemes incur costs associated with deployment and maintenance that ultimately limit their scope of deployment; opportunistic schemes are the key to truly ubiquitous positioning.
While billions of dollars are being spent worldwide on deploying and maintaining new GNSS, there will always be scenarios and environments where these weak signals are blocked or severely corrupted. In these cases, opportunistic sensing powered by smart algorithms running on consumer devices costing a few hundred dollars will be there to fill those gaps.
Ramsey Faragher is a senior research associate at the University of Cambridge and an associate editor for the journal of the Royal Institute of Navigation. Previously he was a principal scientist at the BAE Systems Advanced Technology Centre, near Chelmsford in the United Kingdom, where he developed the NAVSOP GNSS-denied positioning system. His research interests include opportunistic positioning, sensor fusion, and machine learning.
Robert Harle is a senior lecturer at the University of Cambridge with research interests in positioning, sensor fusion, and wireless sensor networks. He has worked on indoor positioning since 2000, developing a series of infrastructure-based and infrastructure-free solutions.
FURTHER READING
• Simultaneous Localization and Mapping
“SmartSLAM – An Efficient Smartphone Indoor Positioning System Exploiting Machine Learning and Opportunistic Sensing” by R.M. Faragher and R.K. Harle in Proceedings of ION GNSS+ 2013, the 26th International Technical Meeting of the Satellite Division of The Institute of Navigation, Nashville, Tennessee, September 16–20, 2013 (in press).
“Opportunistic Radio SLAM for Indoor Navigation Using Smartphone Sensors,” by R. Faragher, C. Sarno, and M. Newman in Proceedings of PLANS 2012, Institute of Electrical and Electronics Engineers / Institute of Navigation Position, Location and Navigation Symposium, Myrtle Beach, South Carolina, April 23–26, 2012, pp. 120-128.
“Efficient, Generalized Indoor WiFi GraphSLAM” by J. Huang, D. Millman, M. Quigley, D. Stavens, S. Thrun, and A. Aggarwal in Proceedings of 2011 IEEE International Conference on Robotics and Automation, Shanghai, May 9–13, 2011, pp. 1038–1043, doi: 10.1109/ICRA.2011.5979643.
“WiFi-SLAM Using Gaussian Process Latent Variable Models” by B. Ferris, D. Fox, and N. Lawrence in Proceedings of IJCAI-07, the 20th International Joint Conference on Artificial Intelligence, Hyderabad, India, January 6–12, 2007, R. Sangal, H. Mehta, and R. K. Bagga (Eds.), published by Morgan Kaufmann Publishers Inc., San Francisco, California, pp. 2480–2485.
“Simultaneous Map Building and Localization for an Autonomous Mobile Robot” by J.J. Leonard and H.F. Durrant-Whyte in Proceedings of IROS’91, Institute of Electrical and Electronics Engineers / Robotics Society of Japan International Workshop on Intelligence for Mechanical Systems, Osaka, Japan, November 3–5, 1991, pp. 1442–1447, doi: 10.1109/IROS.1991.174711.
• Integrated Indoor Navigation
“A Survey of Indoor Inertial Positioning Systems for Pedestrians” by R. Harle in IEEE Communications Surveys & Tutorials, Vol. 15, No. 3, 2013, pp. 1281–1293, doi: 10.1109/SURV.2012.121912.00075.
Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems, Second Edition, by P.D. Groves, published by Artech House, Boston, Massachusetts, 2013.
• Wi-Fi Positioning
“Wi-Fi Azimuth and Position Tracking Using Directional Received Signal Strength Measurements” by J. Seitz, T. Vaupel, S. Haimerl, J.G. Boronat, and J. Thielecke in Proceedings of 2012 Workshop on Sensor Data Fusion: Trends, Solutions, Applications, Bonn, September 4–6, 2012, pp. 72–77, doi: 10.1109/SDF.2012.6327911.
“Comparison of WiFi Positioning on Two Mobile Devices” by P.A. Zandbergen in Journal of Location Based Services, Vol. 6, No. 1, 2012, pp. 35–50, doi: 10.1080/17489725.2011.630038.
• Step Length and Pedestrian Navigation
“Step Length Estimation Using Handheld Inertial Sensors” by V. Renaudin, M. Susi, and G. Lachapelle in Sensors, Vol. 12, No. 7, 2012, pp. 8507–8525, doi: 10.3390/s120708507.
• Computer Vision and Navigation
“Improving the Accuracy of EKF-Based Visual-Inertial Odometry” by L. Mingyang and A.I. Mourikis in Proceedings of 2012 IEEE International Conference on Robotics and Automation, Saint Paul, Minnesota, May 14–18, 2012, pp. 828–835, doi: 10.1109/ICRA.2012.6225229.
• Machine Learning
Information Theory, Inference and Learning Algorithms by D.J.C. MacKay, published by Cambridge University Press, Cambridge, U.K., 2003.
The Bellagio Hotel & Casino in Las Vegas, Nevada. Photo credit: Photographersnature.
Qualcomm and Cisco Collaborate to Improve Indoor Navigation
Las Vegas — home of gambling, shows, and massive hotel/entertainment/resort complexes. It’s not always easy to find what you’re looking for amid miles and miles of indoor floorspace.
Previous Bellagio visitors had to rely on a static map to find their way around the massive Bellagio resort.
In May, Qualcomm Atheros and Cisco showcased its collaboration to enhance indoor location services at a customer deployment at the Bellagio Resort and Casino in Las Vegas. The event took place in cooperation with MGM Resorts International during the Interop information technology conference. Participants had the opportunity to try out Qualcomm and Cisco’s approach to indoor location services, which uses the Qualcomm IZat indoor location platform with Cisco’s Connected Mobile Experience. According to the companies, the combination improves location accuracy and allows users to discover services with context awareness in sprawling retail, travel, and hospitality venues, such as Las Vegas resorts.
The companies began their collaboration in November 2012. The Bellagio mobile app, available for iOS and Android, is now offered as a free download for guests using their smartphones, tablets, and other mobile devices.
At the Interop event, participants were given Samsung devices with Qualcomm IZat software, which tracked their position within the Bellagio on a map as they moved through the hotel — a definite advantage over less-advanced apps which only provide a static map.
Based on the person’s location, the mobile app provides recommendations of nearby services such as restaurants, shows, spa services, and bars and lounges on the property. Guests can become a loyalty member and be alerted to discounts at local restaurants, shops, and wine bars. “This creates a truly unique mobile experience for guests and visitors, putting all the amenities of indoor-location-enabled spaces at their fingertips,” according to Cisco.
Event participants pick up Samsung phones equipped with the Bellagio app.
Qualcomm Atheros, which is Qualcomm Technologies’ networking and connectivity subsidiary, recently enhanced its IZat location platform to enable more precise positioning (within 3–5 meters) inside buildings to make indoor positioning more useful to consumers.
The Cisco Connected Mobile Experience offers a Wi-Fi Passpoint (HotSpot 2.0) solution to integrate indoor location and real-time analytic technologies to deliver personalized mobile services and content. The solution is built upon the Cisco Mobility Services Engine, which uses the Bellagio’s existing wireless access-point infrastructure to determine indoor location for mobile devices. Cisco worked with MGM Resorts’ service provider Mobilitie and its partner Meridian to link the mobile app, context-aware services, and wireless connectivity experience together.
The solution is designed to help app developers deploy mobile applications and services that engage the customer more effectively, the companies said.
