The Wall Street Journal is reporting that Apple has acquired indoor-location company WiFiSLAM. Apple reportedly paid about $20 million for the Silicon Valley-based company. Apple has confirmed the purchase to MacRumors, but offered no details on its plans for the acquisition.
Analysts say this is a sign that the war over indoor mobile location services is heating up.
Apple’s acquisition of WiFiSLAM illustrates how 2013 will be a breakout year for indoor location as initial trials shift to technology deployments, application development, and revenues, according to ABI Research.
Two-year-old start-up WiFiSLAM has developed ways for mobile apps to detect a phone user’s location in a building using Wi-Fi signals, according to the Wall Street Journal. It has been offering the technology to application developers for indoor mapping and new types of retail and social networking apps. The company has only a few employees. Co-founders include former Google software engineering intern Joseph Huang.
“The move comes as Apple continues to build its arsenal against Google in mapping,” according to Wall Street Journal blogger Jessica E. Lessin. “It debuted its own mapping service last year to poor reviews and user complaints about inaccurate data. Apple chief executive Tim Cook apologized for the quality of the product, and Apple has continued to improve it.
“Google already offers indoor mapping in certain locations like airports, shopping centers and sports venues,” Lessin said.
ABI Research’s latest report “Indoor Location in Retail: Where Is the Money?” provides an overview of all major technologies, revenue opportunities and competitive environment. “Analyzing across 10 retail sectors, we are seeing a lot of cross pollination as companies combine handset and infrastructure based Wi-Fi, Bluetooth, and sensor location technologies. The emergence of public venue small cells and carrier Wi-Fi will also create a new wave of opportunity,” commented Patrick Connolly, senior analyst. “As a result, we expect to see a flurry of acquisitions and partnerships in 2013, as major players start to make their moves.”
In support of these technologies, ABI Research is also forecasting smartphone retail apps to break 1 billion downloads, while indoor maps will break 1 million buildings, over the forecast period.
New technology from product development firm Cambridge Consultants can accurately detect someone’s location indoors when GPS drops out. A number of sensors and a custom algorithm determine the location, with an accuracy of within approximately 1 percent of the distance traveled.
The technology uses low-power, low-cost sensors and the device concept is small enough to clip on a belt. It also doesn’t need any existing internal infrastructure.
“We are excited about the many possibilities this cutting-edge technology opens up and the impact it can have in many different situations,” said Geoff Smithson, technology director, sensing systems, at Cambridge Consultants. “It could be used to help locate firefighters in smoke-filled buildings, for example, or to pinpoint the closest doctor in a hospital during an emergency — or to track offenders during home curfews. We are just starting to see the potential of this approach and the diverse demand for this type of low-energy, highly accurate system.”
Indoor tracking systems, which process data from one or more sources of location information to estimate where a person or object is located, are not new. But they often rely on RF signals from Wi-Fi access points or custom infrastructure, poor-quality GPS signals or expensive, high-quality sensors. The availability of low-cost smartphone components — including accelerometers, gyroscopes, magnetometers and pressure sensors — has enabled a new generation of location devices and applications, when combined with a tailored Bayesian algorithm to fuse the information.
The new technology platform can be embedded in an existing design or operate as a stand-alone unit, with options to compute the location locally or transmit the information to a remote system that can process the data before visualizing it on a smartphone app.
“Our biggest challenges were developing an algorithm which optimally combines the data from GPS and the other sensors, and overcoming the issues of using such low-cost sensors in a system without any absolute location reference,” said Smithson.
Cambridge Consultants specializes in developing low-cost, low-power connected devices for clients with a team of experts with sensing, wireless and software engineering expertise. The latest technology builds on the company’s tracking and location systems experience in a variety of market sectors ranging from defense and security to consumer, industrial, and oil and gas.
Pole Star has launched its new indoor location platform, NAO Cloud. NAO Cloud simplifies the deployment of indoor location solutions by introducing an automated deployment process that dramatically reduces time-to-market and the costs of indoor location-based services, Pole Star said.
NAO Cloud integrates the NAO Campus Software Deployment Kit (SDK), and enables customers and partners to deploy NAO Campus, Pole Star’s indoor location solution, in just a few hours, by using cloud-based software tools as well as positioning databases already available and shared by worldwide partner program members.
In addition, third parties will have access to NAO Cloud’s crowdsourcing capabilities, eliminating field interventions for a simpler, faster and more affordable deployment and maintenance process, Pole Star said. Behavioral analytics or geofencing are also supported by NAO Cloud to maximize the monetization of value added location-based services.
The NAO Cloud platform targets a wide range of businesses such as venue owners, advertising platform providers, application developers, global solution integrators or network operators. NAO Cloud makes deployment, integration in mobile apps and maintenance of indoor positioning services a simple process, from a single venue to a worldwide multi-site coverage, Pole Star said.
“The indoor location services market has reached maturity. Multi-venue owners, marketing agencies and major telcos understand the challenges and the value of hyper-local information and real-time interactions with customers and related Indoor Location Analytics. Indoor positioning is the core technology that brings high value,” said Christian Carle, CEO of Pole Star. “NAO Cloud is the result of years of innovation and deep market experience through very large and complex field deployments around the world.”
In 2012, Pole Star achieved several major innovation milestones, such as the integration of Bluetooth Low Energy and Inertial Sensors in its NAO Campus fusion engine, in addition to Map Data, Wi-Fi and GPS signals. The dynamic combination of these technologies provides today the best indoor location performance results in the market, while addressing any type of building and minimizing network infrastructure, deployment and maintenance costs, Pole Star said.
The NAO Campus solution is now available for more than 80% of the smartphone market, compliant with Android and iPhone devices and embedded in consumer applications on the Google Play Marketplace and the Apple App Store.
Today, Pole Star’s indoor location solutions have been deployed in more than 43 million square feet, in 15 countries such as airports (Paris Charles de Gaulle), shopping centers in Europe and North-America, museums and department stores. In 2011, Pole Star opened its North American headquarters in Palo Alto and has expanded its international presence in 2012, building deep partnerships with companies in Europe, North-America, Asia, Australia and the Middle East. Finally, at the end of 2012, in time for the holiday season, Pole Star launched, its “living lab” mobile application, Mall Buddy, that covers 9 of the biggest malls in Silicon Valley, from San Francisco to San Jose and demonstrates the worldwide extension capability of Indoor location services.
Skyhook and Philips Lifeline have announced a collaboration to incorporate Skyhook’s hybrid location positioning platform into Philips’ Lifeline GoSafe mobile personal response services. Skyhook’s hybrid location service will be part of a suite of locating technologies used with the new GoSafe system and designed to help provide the call center with the location information needed to support locating of users in the event of an emergency.
“Accurate location information is of critical value to ensuring the quick dispatch, arrival and delivery of what is often life-saving assistance,” noted Rob Goudswaard of Philips Home Monitoring. “After reviewing the market, we concluded that Skyhook’s location network and technology capabilities were consistent with our requirements for enabling timely and accurate response.”
“If an individual experiences a fall or other emergency, quickly getting help to the right location is of vital importance,” said Michael Shean of Skyhook. “Skyhook is proud to partner with Lifeline, the leading medical alert service, in order to enhance the safety and care that Lifeline provides to all of its customers.”
In December 2011, Grizzly Analytics released its first comprehensive report on indoor location positioning technology, predicting that indoor location services were ready to revolutionize the mobile market. The five months that followed have shown how true this was, with new initiatives announced on a regular basis and numerous demonstrations at industry conferences, Grizzly Analytics says.
In a fully revised and updated 163-page report, Grizzly Analytics gives an up-to-date analysis and comprehensive overview of indoor location positioning R&D. Included is information on the research activity of all the major mobile companies — Google, Microsoft, Samsung, Apple, Nokia, RIM, Cisco, Qualcomm, Broadcom, STMicroElectronics, Sony Ericsson and others — and also more than 30 start-up companies that are actively bringing indoor location services to market.
“These technologies are poised to revolutionize smartphone usage by enabling GPS-style mapping, navigation, local search, check-ins, location-sharing and other location-based services to work indoors in malls, megastores, offices, airports, casinos and other big indoor places,” according to a statement by Grizzly Analytics. “Indoor location will also transform commerce, enabling searching for items on store shelves, sending deals and promotions to nearby customers, advertisements for nearby stores in malls, and more. Location services are also entering the enterprise, with indoor asset tracking, employee search, and more.
“In this updated technology trend report, Indoor Location Positioning: Research Pipelines, Start-ups and Predictions, Grizzly Analytics answers the questions you have about this new technology. What approaches are being researched by different companies? Which companies have mature research? What are the gaps in each company’s research that they are likely to fill by acquiring start-up companies? Which start-up companies are likely to be acquired or to emerge successful in the market? What areas of technology are not yet addressed by start-ups, and remain open to new entrepreneurs and investors?”
Get out of the way, GPS. Wi-Fi is elbowing in on the location game. Wi-Fi operators are tracking people and offering retailers and marketers access to customers’ behavior and location. Traffic patterns emitted by smartphone Wi-Fi signals let network operators keep tabs on what shoppers are doing. Heat maps are being created with data from Wi-Fi points to map out aggregated customer behavior. Nearbuy Systems offers stores software that will let them track the website that a shopper is viewing, overlaid by where the shopper is within the store. However, beware of companies’ hyped up claims on indoor location. Another worry is the deployment of proprietary location systems which reduce overall usefulness. And some offerings are simply PowerPoint aspirations. In other news, Apple and Google are kings of the hill; in-vehicle mapping belongs to Nokia; and location privacy of a different sort.
Fragmented Indoor Location. If proprietary indoor location systems are developed, the market will be hampered. Ben Rodilitz of Level8 noted that, while attending GPS Wireless last March, he was bemused by the excitement regarding indoor location as manifested in a number of one-off, proprietary systems. If Home Depot used its own system, an airport used another, and a shopping mall implemented a third, ubiquitous indoor location would be problematic. “I know companies like Qualcomm, Broadcom, and SiRF/CSR were building competing platforms; one would hope this is a vehicle for best-of-breed choices for service providers,” says Rodilitz. I am glad to see the formation of the In-Location Alliance and the players who are supporting it.”
Other Complications. The nuts and bolts of indoor location aren’t easy peasy. “For detailed location pinpointing in places like malls, a high density of Wi-Fi radios need to be deployed and it isn’t super cheap to do so,” says Joseph DeStasio of Boingo Wireless. Stores may want to deploy a denser Wi-Fi system than in the outer mall. But it can be a clunky transition between two different Wi-Fi systems. DeStasio estimates that true mobile retail location-based advertising/couponing at malls is still 18 months away.
Mapping in Vehicles. Nokia may be battered, but the mapping it acquired years ago from its acquisition of Navteq is shining bright. Companies have long fought over “ownership” of the in-dash navigation market, and Navteq lords over the market, powering four out of five systems. Nokia has deals with many car makers, including BMW, Hyundai, Mercedes, and Volkswagen, as well as with Pioneer and Garmin.
Wireless Data Privacy and Mooching. There is always an interesting mobile location privacy case. In Pennsylvania, police obtained a warrant to search the house where child pornography was being downloaded. Police determined that the offender was a neighbor who had been free-loading on the house’s wireless Internet. The suspect was found with Moocherhunter, an app to identify wireless moochers. The suspect argued that police needed a warrant to use the app to locate him. The court ruled that he “could have no reasonable expectation of privacy in the signal he was sending to or receiving” from the wireless router.
More on Wi-Fi. Towerstream is building wholesale Wi-Fi access points across some urban regions, including Manhattan, with 1,000 access spots arranged in a giant dense honeycomb across the Big Apple. Before you equate this with previous municipal wireless disasters, know that these networks are several times fasters and don’t involve local government.
Towerstream is granting users four hours use with no charge if the user will interact with a location specific advertisement. These deals may be targeted to within dozens of feet of the user. Since service over Wi-Fi doesn’t count against U.S. mobile data limits, usage is particularly appealing to 18-34 year olds, who may be wallet constrained and open to viewing location-based ads in exchange for streaming video at high speeds.
Oligopoly! Google’s Android and Apple’s iOS continue to wipe the floor with their competition. Together they controlled 87.9 percent of the U.S. smartphone market in October, according to comScore. Android ended October with 53.6 percent nationwide smartphone share, increasing 1.4 percentage points over July. iOS grew its U.S. market share from 33.4 percent in July to 34.3 percent in October, a 0.9 percent improvement.
Tweet This. Use of social media and social networking is growing rapidly. Consumers continue to spend more time on social networks than on any other category of site—roughly 30 percent of total time online via mobile, reports Nielsen and NM Incite. Facebook remains the top social network, followed by Twitter and Blogger, but new social media sites continue to emerge.
Foursquare Wants Money. The tepid, if not poor, performances of social media IPOs has made investors skittish. The fates of Facebook, Zynga and GroupOn stocks have weighed heavily on this category. Foursquare, which pioneered location check-ins and is now succeeding with target location couponing, is having difficulty attracting added investment, reports the Wall Street Journal. Foursquare counts more than 25 million registered users, with only about 8 million accessing the app monthly. Some investors believe the company is moving too slowly to monetize.
In this column, I normally write about satellites, signals, and space (as in outer), and the policies or controversies pertaining to those entities. This week we are headed indoors. Inner space, where GNSS has difficulties going, but must go, somehow, to prove itself commercially and governmentally. To do so, it needs powerful friends.
The most rigorous indoor location testing to date got underway two weeks ago in the San Francisco Bay Area, in trials organized by a Federal Communication Commission’s (FCC) advisory committee, the Communications Security, Reliability and Interoperability Council (CSRIC). The tests seek to lay the groundwork for future FCC rulings on indoor location requirements, to which wireless carriers must adhere. The trials run through December 31, in dense urban, urban, suburban, and rural test blocks around the Bay.
For the sake of the GPS/GNSS industry and community, whatever technology solution emerges from these trials as the favorite, GPS/GNSS had better prove itself as a part of it, not only to gain a foothold in indoor markets and applications, but to preserve its standing in outdoor environments. Other positioning technologies have sprouted up like mushrooms, filling in vacant micro-niches. The indoor environment as a whole is just that, an environment, not a niche, and where it goes — taking the money with it — outdoor may likely follow. Wi-Fi, for example, is gaining installment base by leaps and bounds, and probably currently supplies the best unaided indoor location — where it is installed.
“Retailers are desperate for more customer data, this [indoor location data] is golden,” says Janice Partyka, GPS World’s contributing editor for wireless. “They probably won’t wait for the requirements or for the wireless carriers to push out the solution. Some venues like airports can track you now. This time around, commercial uses will precede E911.”
Although the need for accuracy is arguably greater indoors, so too are the difficulties — and the costs. At stake is getting room-level and floor-level location accuracy from a mobile 911 call to emergency responders during the Golden Hour, a term used in heart-attack, stroke, and trauma situations, but which applies equally to fires, violent crimes, and virtually by definition to any sort of emergency. Responders need to know “which side of the wall” he/she/it is on, and which floor — even before they enter the building.
In the floor-level or vertical component of the location coordinates resides one of the key challenges. The vertical or Z-coordinate in a GPS/GNSS solution has always had the lowest degree of accuracy. To be sure, the barriers imposed by steel, glass, and concrete, as well as the confusion generated by multipath in dense environments, apply just as much to the X- and Y-axes, but getting to Z (since getting from floor to floor in case a mistake is made would be most time-consuming) may constitute the largest challenge.
The FCC hosted a workshop in Washington D.C. on October 24 in preparation for the tests. The workshop introduced public-safety officials’ expectations for indoor coverage, test mechanics, the technologies under test, and more. CSRIC will draft a report for the FCC based on the test results by March 2013.
The Candidates, Please. Four companies are actively participating in the CSRIC tests, submitting their diverse indoor solutions for rigorous and repeatable performance proof: Boeing, NextNav, Polaris Wireless, and Qualcomm.
The CSRIC test bed discussions started in 2010 with seven potential technologies for Stage 1:
Polaris Wireless (RF fingerprinting)
Qualcomm (assisted-GPS/AFLT/cell ID)
NextNav (Wide-Area Positioning System (WAPS) of GPS-like terrestrial beacons, described here.)
Boeing (low-Earth orbit Iridium satellites; because much closer to Earth than GPS, hence 30-dB penetration margin; a range of Iridium solutions, some of them in combination with GPS
CSR (AGPS/WiFi/MEMS)
TruePosition (UTDOA)
CommScope (DAS proximity).
The latter three have since dropped out of the testing for reasons not stated.
Polaris Wireless is the only cellular-network-based location technology provider in the tests, as all other network-based location technology providers withdrew from participation in the CSRIC trials. The trial includes Polaris Wireless’ Wireless Location Signatures (WLS), a software-based radio-frequency (RF) pattern-matching approach that requires no changes to the wireless device or the wireless service provider’s base stations. The June issue of GPS World carried an article on this technology; see “Location by Database.”
Norman Shaw, Polaris Wireless executive director of government affairs and business development, serves as co-chairman of CSRIC’s efforts on improving indoor location technology. “RF does funny things. But there are cultural issues as well. It’s natural for us to expect technology to get us all the way to the goal line. However, we often overlook the challenges. Can we deliver Z-location? And can we do it in an actionable way for the emergency responder? That person needs to know, not that the emergency is 185 meters above the ground, but the number of the floor. For this and for other reasons, you need to marry different technologies.”
“This test is a great start,” Shaw concludes. “But this test bed will need to be maintained to continue testing and to test future technologies. Additionally, a second test bed will be needed in a denser, older city, probably East Coast; perhaps Chicago or New York. We should all be aware that once the testing concludes and the regulations appear, this is the emergency service we’re going to be living with for the next 20 years.”
Ganesh Pattabiraman, co-founder, president, and chief operating officer at NextNav, adds that in addition to providing data to drive regulation, the testing “brings awareness to the public safety operators and the FCC that here are reliable technologies that can address the problem of indoor location. As opposed to 10 years ago, or even six years ago. Not just ours, but others too.”
According to the NextNav website, “For devices equipped with NextNav’s technology, when a subscriber calls 911, the first responder won’t be left guessing about where they are. Providing a unique height capability, with vertical precision of up to 1 – 2 meters, first responders can move rapidly to the correct floor to ensure that not a second is wasted in the emergency response process. NextNav’s transmission is encrypted, secure and is available for carriers as a standalone service for E911 only. A carrier can implement the NextNav solution to enhance location performance of the E911 system separate from any decision to use NextNav capabilities as part of their commercial location-based services.”
Pattabiraman continues, “The need for accurate indoor location is greater [than for outdoor], but is the technology and the cost to the wireless carriers of implementing it up to the task? It all comes down to economics. If we or anyone can provide a solution that is incremental, reasonably priced, and commercially viable, then we can move forward.”
Particularly, he adds, “If we can build on the existing blocks of GPS at minor incremental cost, then we see the possibility of delivering the best possible accuracy for the lowest price.”
Test Administrator and Parameters. TechnoCom, a location-technology-neutral business, is conducting the Bay Area tests. TechnoCom is an active contributor to the Alliance for Telecommunications Solutions (ATIS) Emergency Services Interconnection Forum (ESIF). The ATIS conducts long-term research that serves as a basis for CSRIC findings and recommendations. The two organizations have many of the same members, although CSRIC consists of FCC-nominated members who serve one-year terms and thus doesn’t have “the consistency needed to do good science,” in one participant’s words.
The TechnoCom test parameters consist, broadly, of: a variety of locations (environments) and building types (also known as morphology), multiple test spots in each building, and each test spot to have at least 100 test calls. Researchers are looking for an indoor ground truth accuracy of 3 meters, something that would warm the hearts of public safety responders, but a level which, other experts say privately, is highly unlikely to be implemented as a requirement.
Public safety advocates would ideally want 5 meters, to the extent of “knowing which side of a wall a heart-attack victim is lying on.” Technology vendors such as those supplying solutions for test would probably settle for a 50-meter requirement, even if their solutions can do better. That’s at least in part because they are caught between the public safety folks on the one side and the wireless carriers — to whom they must sell — on the other. The wireless carriers are the most conservative of all, and may not want anything more stringent that the current outdoor requirements: 50-meter accuracy 67 percent of the time, and 150 meters 90 percent.
TechnoCom will test the following locations:
Dense urban: a four-block area north of Market Street in San Francisco’s financial district; as one participant pointed out, this is still not the densest urban environment to be found in the United States. For that, you have to look at older, Eastern cities such as New York or Chicago.
Urban: San Francisco and downtown San Jose
Suburban: Santa Clara County (malls, homes, condos and some high-rises)
Rural: Between Gilroy and Hollister, California.
All kinds of structures, about 20, typically found in the four basic environments, will serve as test spots: high-rise, mid-rise, mall, apartment building, house, warehouse, and barn. Various test points will be sited in each as appropriate, probably at 5-floor intervals in multi-storey buildings.
This is the next frontier for personal and machine navigation — and many are out there now, working diligently on it. In just one example, a new chip fuses input from several sensors, using the best combination at any given time to maximize coverage and accuracy while keeping power draw to a minimum. This produces continuous position availability in indoor environments, as demonstrated by performance measurements in real-world test environments.
The senior product manager responsible for this development joins us to talk about the inner workings and the outer manifestations of this new solution. He’ll be joined by other guest experts to be announced.
J. Blake Bullock was senior product manager responsible for CSR’s next generation of GNSS solutions. He has now transferred to Samsung System LSI Business and is responsible for GNSS and indoor positioning solutions. He holds a M.Sc. degree in geomatics engineering from the University of Calgary, an MBA from Arizona State University, and several patents in LBS and navigation.
By J. Blake Bullock, Mahesh Chowdhary, Dimitri Rubin, Donald Leimer, Greg Turetzky, and Murray Jarvis
A new chip fuses input from several sensors, using the best combination at any given time to maximize coverage and accuracy while keeping power draw to a minimum. This produces continuous position availability in indoor environments, as demonstrated by performance measurements in real-world test environments.
Users of GPS receivers in smartphones and many other consumer electronic devices expect these devices to work in all environments, including dense urban canyons, parking garages, and indoors, enabling a wide range of location-based services such as mapping, search, tracking, and navigation. Recent advancements in assisted-GPS (A-GPS) technology have enabled improved positioning indoors, but GPS receivers are still not sensitive enough to determine position everywhere that users go.
Several consumer products now use GLONASS and assisted-GLONASS (A-GLONASS) measurements to improve coverage and accuracy of GPS receivers. We refer to such combo receivers as GNSS receivers here. GLONASS measurements have similar characteristics to GPS measurements in that they are subject to blockage and multipath. In dense urban canyons, GLONASS measurements help to improve availability and accuracy of a position solution. However,GLONASS provides little performance improvement indoors.
Various emerging technologies for indoor positioning use installed wireless transmitters as beacons for making measurements for positioning. Existing Wi-Fi access points (APs) can be used in this way to determine position when indoors. Other solutions include the emerging Bluetooth Smart transmitters, GSM, 3G, and other mobile phone transmitters, the NextNav network, and other dedicated beacons for indoor positioning. Each technology has advantages and disadvantages for use as an indoor solution, to be discussed here.
The SiRFstarV location chip with SiRFusion combines A-GPS and A-GLONASS advances with Wi-Fi positioning and dead reckoning using low-cost micro-electro-mechanical systems (MEMS) sensors. Smartphones, tablets, cameras, fitness products, and other consumer electronics are equipped with an increasing array of MEMS sensors including accelerometers, magnetometers, gyroscopes, and barometers. The SiRFstarV chip acts as a gateway to receive input from all available MEMS sensors so that the output signals can be combined with the GPS, GLONASS, and Wi-Fi measurements that give absolute position. The observations from all these sources are fused together using a Kalman Filter. Smart location management makes use of the best combination of sensors at any given time to maximize coverage and accuracy while keeping power draw to a minimum. This produces continuous position availability in indoor environments.
Target Performance and Use Cases
The last 10 years have seen great improvements in GPS positioning indoors, primarily driven by the mobile market and the FCC E911 directive to be able to locate mobile-phone users. Today, it is possible to locate a mobile phone indoors using A-GPS, advanced forward link trilateration (AFLT), or Wi-Fi positioning. Typically it takes several seconds to determine a fix indoors, and the accuracy is not as good as outside. It is also not feasible to get continuous position updates for use in tracking, fitness, or navigation systems.
Wi-Fi positioning has improved the availability of fixes indoors and also the time to get a fix. However, today AP positioning is based on surveys that have been done using GPS vehicles outside, so the determined positions tend also to be outside, even when the mobile device is indoors.
To reliably deliver indoor positioning, the positioning system must be able to:
◾ Determine position quickly — within a few seconds.
◾ Determine position accurately — within 5–10 meters, circular error probable (CEP) 50 percent.
◾ Determine position updates at 1 Hz.
◾ Preserve battery life.
Cameras have very different uses than handsets. Typically, a camera is off until the user is ready to take a picture or video. When a picture is taken, theposition can be recorded and used to geotag the image with the location, date, and time. For this use case, the positioning system needs to be able to determine position indoors quickly and with low power, but continuous updates at 1 Hz are not needed.
Fitness products use location for recording distance traveled, speed, elevation, calorie counting, and showing a track of running or cycling workouts. Users value good accuracy and a fast startup time when they are about to begin a workout. The positioning system needs to be able to determine position continuously, but not necessarily show the position updates in real time.
Battery life for a typical assest-tracking device is extremely important, as is the ability to locate the asset in any environment. Continuous position updates are not needed. A typical feature of asset-tracking systems is the ability to set a geofence boundary, used for generating alerts. The positioning system needs to determine position periodically and compare with the geofence. If the position is outside the geofence, an alert is sent to the user.
GNSS Positioning
Positioning algorithms on the SiRFstarV Quad-GNSS combine range measurements from all-in-view GPS, GLONASS, QZSS, and SBAS satellites. The chip is hardware-ready to enable Galileo and Compass measurements with a future software update. Immunity to interference, cross-correlation, and multipath impairments are provided to achieve very high sensitivity, which is critical for indoor positioning. Nevertheless, the utility of reception sensitivities below –165 dBm has been found to have limited value for all but static cases, due to the very long integration times required to make reliable measurements. Increasing the number of independent range measurements helps improve indoor positioning, and using multiple constellations is a key enabler to provide them.
The improvement in indoor positioning by using multiple constellations is similar to the improvement in urban canyon positioning, since the impairments are similar.
One significant difference is that multipath delays for indoor environments are typically much shorter, and conventional mitigation methods cannot be applied without a very wide RF bandwidth. The shorter delays therefore produce lower signal levels due to phase cancellations and pseudorange bias errors, which are recognized as multipath errors and reduced as part of the chip’s measurement processing. While the advantage of augmenting GPS measurements with GLONASS is typically 20 to 40 percent improvement in position accuracy in urban canyon environments, it shrinks to only 7 to 15 percent indoors. Even with GLONASS measurements, the position is frequently shown outside of the building.
Figure 1 shows the results of an indoor walk test with a SiRFstarV receiver using GPS and GLONASS. The test was done on multiple floors of a three-story commercial building. Table 1 shows a summary of the performance metrics as determined by stopping at benchmark locations during the test. Fixes are available nearly 97 percent of the time. The addition of GLONASS tracking increased the average number of satellite measurements from 7.3 to 9.9 and improved the horizontal and vertical accuracy by about 7 to 15 percent. The horizontal accuracy is about 11.5 meters, 50 percent CEP. However, more than half the fixes are shown outside of the building.
Table 1. Impact of GLONASS on indoor positioning.
This test had high availability, but many environments cannot provide GNSS signals with sufficient energy to obtain position fixes. While the use of multiple constellations improves the accuracy and availability of the GNSS fixes, additional position sources are needed to achieve suitable availability and accuracy for continuous indoor positioning.
MEMS Pedestrian Dead Reckoning
Pedestrian dead-reckoning (PDR) logic is realized using integration of MEMS sensors with the SiRFstarV GNSS receiver, which has a dedicated I2C port designed to interface with MEMS sensors. A data-acquisition task collects sensor data and performs low-level error checking, timing synchronization, and buffering of the data from various sensors. This data is sent periodically to the process where a sensor data handler prepares it for further processing.
Acceleration data is processed by the context (or user mode) detection algorithm to determine the dynamic state of the user (or receiver) in order to select appropriate position-determination algorithms and associated motion parameters used by these algorithms. The PDR algorithm is employed when the user mode is classified as walking, fast-walking, jogging, stationary, climbing/descending stairs, elevator, and escalator.
The generalized navigation equation can be written as
(1)
where vne is ground velocity in navigation frame, Cnb is direction cosine matrix relating body reference frame to navigation frame, f b is specific force, ωnenis turn rate of Earth, ωnenis body rate, andgnlis local gravity vector expressed in navigation frame. This equation (in navigation frame) relates the ground speed of an object to measured specific force and measured body rate. The generalized navigation equation, when integrated twice, transforms from the acceleration of the platform into position represented in North and East reference frame, results in Equation 2,
(2)
where, s(t) is displacement and ψ(t) is heading. In the case of pedestrian motion, velocity and heading can be assumed to be constant during the interval when a step is taken. With this assumption, the integral form of Equation 2 can be rewritten as a difference equation with piece-wise linear approximation.
(3)
This equation describes a method of dead reckoning (DR) that is based on step counting rather than integration of acceleration and angular rate. This PDR process consists of three important components: the previously known absolute position of the user at time t-1 (Et-1, Nt-1), the stride length or distance traveled by the user since time t-1 (), and the user’s heading (ψ) since time t-1. The coordinates (Et, Nt) of a new position with respect to a previously known position (Et-1, Nt-1) can be computed as shown in Equation 3. The position initialization of the PDR process can be accomplished using any or a combination of absolute positioning technologies such as GNSS, Wi-Fi, or GSM.
Performance of PDR algorithms is dependent on obtaining calibrated MEMS inertial sensor data continuously. Calibration of sensors is accomplished through collecting and processing sensor data for user motion of device in Earth’s gravity and magnetic field. Accelerometer and gyroscope calibration logic utilize the knowledge of device stationary condition. Magnetic sensor calibration logic requires that various axes of sensor are exposed to Earth’s magnetic field vector at the user location. With the given time and location estimate, the Earth’s magnetic field parameters are computed using the World Magnetic Model. Normal use of a mobile device would result in rotations in various Euler planes thereby applying Earth’s magnetic field to various axes of magnetic sensor. Earth’s magnetic field parameters are also used to detect occurrences of magnetic disturbances. Magnetic sensor measurements are de-weighted for the PDR process during such magnetic disturbances.
The essential logic components that affect the performance of PDR positioning system are: calibration of sensors, step detection, determination of walking direction, positioning fusion logic, and orientation of phone while walking. Typical phone users will have the phone in a pocket, in a belt clip, in a purse or bag, in their hands looking at it, or up to their ear in a conversation. The PDR algorithms need to be able to perform robustly in any of these orientations.
With PDR, an absolute position can be propagated as a user moves on foot. Due to the error growth characteristics of typical MEMS devices used in consumerelectronics, the estimated path deviates from the actual path as a function of distance traveled. The error growth is typically on the order of 10 percent of distance traveled, especially in the presence of magnetic disturbances. This level of error growth makes MEMS PDR unsuitable as the sole positioning solution when indoors. Periodic absolute positioning updates are required to correct the path and to allow additional calibration.
Wi-Fi Positioning
Opportunistic positioning using observed Wi-Fi signals is a well established method of absolute positioning in GNSS-denied environments. Off-the-shelf Wi-Fi access point hardware is not well suited to positioning using timing observations, therefore the chip under discussion uses observed signal strengths together with the broadcast unique identifiers (BSSIDs) as the basis for the Wi-Fi positioning sub-system. Signal strength information is by its nature asymmetric. A strong observation of a Wi-Fi AP indicates that one is near it, but it is not safe to infer from a weak observation that you are far away. This is because weak observations may be due to, for example, occlusion, fading, or antenna orientation. This means that the performance of Wi-Fi positioning varies considerably with location and time, especially in areas with many pedestrians.
There are several limitations to Wi-Fi positioning. The first is that since it is opportunistic, there is no guarantee of performance. Fortunately, AP density is typically highest in the areas where Wi-Fi positioning is most needed, namely, deep indoors and in dense urban areas. Secondly, there is no guarantee that APs will remain in the same locations. APs may be attached to mobile devices, or AP equipment may simply be moved. This leads to a requirement for the database of AP locations to be dynamically monitored and continuously improved. Lastly, the location of the APs is not known a priori, and hence there needs to be some independent means of locating the APs in order for them to be used for positioning. The CSR server implementation uses the other technologies present, namely GNSS and MEMS, to generate this information. This avoids the need to manually survey areas where Wi-Fi positioning coverage is required.
The chip supports Wi-Fi receive (sniffing) and positioning via scanning of the ISM band to detect any broadcast 802.11b Barker codes on any of the 14 channels. This process takes approximately 100 milliseconds/channel, producing a scan time of 300 milliseconds for the three primary channels, or a scan time of 1.4 seconds for a systematic scan of the entire band.
The usual configuration is for the SiRFstarV chip to be connected to the CSR Positioning Center (CPC) server via software running on a host processor in the device. On request, the CPC can then provide the device with all the APs known to be in the vicinity of the user. This data is sent as a sequence of spatially contiguous sets of APs in a tiled structure. The benefit of serving tiles to the user, rather than user’s position or only the APs instantaneously detected, is that the client device can subsequently operate independently with only occasional server contact. In fact, since the chip supports on-board storage of the AP tile information, it can also operate for extended periods without waking up the host, a feature useful for low-power geo-fencing and other location functions.
Another important aspect of the CPC is that is supports crowd-sourced learning of Wi-Fi APs. Client SiRFusion devices submit anonymous sets of Wi-Fi signal strength data and associated BSSIDs, together with contemporaneous GNSS and relative information from the MEMS devices. By collating all the information available in an area across users, the system is able to calculate the most likely locations for Wi-Fi APs and hence generate tiles available to provide to all users. Unlike crowd-sourced systems based on GNSS alone, CSR also uses relative data from MEMS PDR to extend the coverage area of the crowd-sourcing indoors. This produces better Wi-Fi positioning performance indoors.
Sensor Fusion
The GNSS, Wi-Fi, and MEMS PDR solutions offer varying levels of accuracy, coverage, and reliability. CSR has developed SiRFusion, a Kalman filter-based fusion engine in the SiRFstarV device, to combine all these location inputs. Sensor fusion is a critical component and does the job of fusing the multiple sources of position information to provide a single best estimate of position and confidence to the user. It takes as input absolute positions from GNSS and Wi-Fi and also any relative information derived from the MEMS PDR sub-system. Figure 2 illustrates the major components of SiRFusion.
Figure 2. Major components of SiRFusion.
To determine how to weight and smooth the different inputs, it is crucial that the individual input technologies provide reliable estimates of their confidence and correlation. As an example, we mentioned earlier that the quality of Wi-Fi positioning is variable and is best when strong APs are seen. A high quality Wi-Fi position, signified by a high confidence value, will cause the fusion filter to be strongly biased towards this positioning source. When the Wi-Fi position quality subsequently deteriorates, this is reflected in a lower position confidence, and hence the fusion filter down-weights Wi-Fi influence. In turn, this allows dominance of the MEMS PDR input until another sufficiently high-quality absolute position allows the filter to correct. The net effect of this behavior is that the MEMS bridges the position output smoothly between high-quality absolute position fixes and to a first approximation, any low-grade information is ignored. Another benefit is that individual Wi-Fi positions can be jumpy, because on an individual scan there is considerable variation in the audible APs and their signal strengths. Sensor fusion with MEMS PDR helps to smooth this out, providing a continuous trajectory and a more satisfying user experience.
Another job of the fusion engine is to transition smoothly from indoors where Wi-Fi and MEMS PDR dominate, to outdoors where GNSS dominates. This happens automatically in the fusion filter with the GNSS becoming increasingly dominant outdoors as GNSS confidence improves. Conversely, the Wi-Fi position accuracy will typically decrease outdoors and the dominant technology will therefore gradually dominate the solution. When technologies are not being used they can be switched off or placed in a maintenance mode to reduce unnecessary power consumption.
Performance Results
CSR has developed a demo platform with SiRFstarV and SiRFusion in a modified HTC Google Nexus One handset with Android. Figure 3 shows a modulewith the receiver and MEMS devices; the module is mounted inside the HTC phone shown in Figure 4. The data log includes PDR output, Wi-Fi positioning, GNSS positioning, and the combined sensor-fusion solution.
Figure 3. Module with MEMS devices.Figure 4. HTC Google Nexus test phone.
A series of tests were carried out in Tokyo Station in Tokyo, Japan. The tests shown here were all done on the B1F level in the shopping area adjacent to the station. This area is two levels below the tracks and is below ground. There are no windows, and there was no GNSS reception. The environment also has lots of magnetic anomalies due to tracks, trains, elevators, escalators, and many people in motion, which affects Wi-Fi signals. Each plot shows an indoor map superimposed on the Google Earth image of the area. The narrow aisles in the map are about 5 meters wide. The map is used for presenting results only; it was not used to do map-aiding or map-matching.
AP harvesting and learning was done in this area before the tests were conducted. In each test, the phone is turned on, and SiRFusion uses Wi-Fi measurements and data from the AP database to determine the initial position without any assistance from GNSS. In each case, the initial position was determined within 1–3 seconds.
In Figure 5, the route walked is shown by the straight green line, with the start point in the lower left corner. Wi-Fi positioning is shown in red, the yellow isthe MEMS PDR solution, and the blue shows the SiRFusion solution, which in this case is combining Wi-Fi and PDR. The Wi-Fi position is not available every second and at times has discontinuities of several meters. This is due to the signal variability as discussed previously. The PDR solution shows a gradual drift that is more than 25 meters off track in places. This is not an issue for SiRFusion, as only the relative positioning is used from the PDR output. The SiRFusion solution shows a smooth continuous output that has a maximum cross-track error of about 7 meters. Note that the error of the SiRFusion solution does not follow the PDR solution. The absolute positioning provided by the Wi-Fi fixes keeps the solution on track.
Figure 5. Tokyo Station test showing Wi-Fi (red squares), PDR (light green squares), and SiRFusion output (blue); straight green line shows true path followed.
Figure 6 introduces a test with several turns in the corridors. The path walked is marked by the red flags, and took just under six minutes. The fusion solution is shown in blue. The start point was in the lower left. The fusion solution was able to detect each of the turns made while walking. The shape of the path clearly follows the marked path walked. The largest deviation from the path was ~7 meters. Typically, the solution was within 5 meters of the path walked.
Figure 6. Tokyo Station test showing turns; red flgas mark actual path, blue is SiRFusion output.
Figure 7 shows another path through the corridors, this time just over seven minutes in duration. Again, the fusion solution shows each turn correctly and in this case, the maximum cross-track error is about 5 meters. Figure 8 shows the same path, but with the output from three separate walks shown in green. A cold start was done before each walk. The results agree closely, showing high repeatability between test runs.
Figure 7. Tokyo Station test showing turns; legend as per Figure 6.Figure 8. Tokyo Station test repeatability; light green shows three successive SiRFusion test runs.
To obtain a quantitative measure of the performance accuracy, the locations of several points in the Valley Fair Mall in Santa Clara, California, were determined. During several independent test runs in the mall, the tester went to each designated test point and indicated a marker in the log. The measured positions were compared with the determined positions to generate the performance statistics shown in Table 2. The cross-track error was 3.2 meters 50 percent CEP and 13.1 meters 95 percent CEP. These levels agree with the estimated results determined from the maps in the Tokyo tests.
Table 2. Accuracy test, Santa Clara Mall.
These tests show excellent results in availability, accuracy, stability, and repeatability. The availability is near 100 percent, with the only missing fixes being the first couple of seconds on startup. The position accuracy is sufficient to guide a user to the correct storefront, terminal, or track in a complicated indoor environment. The smooth continuous output can be used for voice guidance applications.
Applications
Continuous indoor positioning enables important consumer and commercial applications including indoor search, navigation, social networking, andadvertising on mobile devices, indoor geotagging on camera devices, indoor workout monitoring on fitness devices, and asset tracking.
Mobile Devices. Search, mapping, and navigation are popular uses for smartphones, tablets, and other mobile devices. These services are even more powerful when taken indoors in shopping centers, airports, train stations, and other public places. In a large shopping area, a consumer can search for the nearest store with items of interest and get walking directions to that store. He or she may receive a coupon or ad relevant to the store or item that they searched for. Business owners are interested in targeted mobile ads to help connect with interested shoppers.
Camera Devices. Location capability is emerging on camera devices for geotagging the location where a photo was taken so that it can be embedded with other meta-data in the image file. Geotagged photos can be easily shown on maps, sorted by location, and shared with others. Indoor positioning enables geotags to work inside as well as outside, completing the coverage availability.
Fitness Devices. Fitness watches and other workout tracking products use location to measure distance traveled, calories burned, steps taken, and plot workout tracks on maps. With indoor positioning, indoor workouts can also be included in consumers’ data analysis as they track a wider variety of workout types.
Machine-to-Machine and Asset Tracking. The benefits of indoor location extend the asset-tracking model from fleets of trucks and automobiles to include all types of valuable assets, from children to pets to merchandise and even data. It is valuable to provide an individual with their own location, but it is even more valuable to provide the location of objects that are somewhere else in an M2M application. The low-power, ubiquitous location capability of SiRFstarV and SiRFusion allows very small tags with months of battery life to be attached to virtually any object and in combination with an appropriate communication link (cellular, Wi-Fi or BLE) report that position to the CPC. From there, a cloud-based location service to carriers, retailers, malls, government agencies and others can add location to their product mix. This service can even be extended to provide data security so that sensitive corporate information could only be accessed by devices within an authorized area, and not in a public place such as an airport. By making ubiquitous location information available on almost any imaginable platform, the use cases are nearly limitless.
Conclusion
Sensor fusion algorithms have been developed and refined to address the problem of determining position indoors. Performance testing shows that the position availability approaches 100 percent, and accuracy exceeds 10 meters, 50 percent CEP. The fusion technology is suitable for integrating in a wide range of consumer and commercial devices. The solution uses existing wireless infrastructure and can be deployed around the world with no new equipment to install or surveying to perform. The self-learning capability adapts to changes in the signal environment.
Acknowledgments
Seiji Ishikawa and Shinya Ohno of CSR performed the testing in Tokyo Station and were instrumental in preparation and analysis.
ST Microelectronics provides the MEMS sensors used in much of CSR SiRFusion testing.
J. Blake Bullock was senior product manager responsible for CSR’s next generation of GNSS solutions. He has now transferred to Samsung System LSI Business and is responsible for GNSS and indoor positioning solutions. He holds a M.Sc. degree in geomatics engineering from the University of Calgary, an MBA from Arizona State University, and several patents in LBS and navigation.
Mahesh Chowdhary is senior director MEMS technology at CSR where he works on the integration of GPS, MEMS sensors, and wireless technologies. As founder and CTO of Acculeon, he pioneered the use of GPS and MEMS sensors in vehicle safety applications. He received his Ph.D. in Applied Science from The College of William and Mary, Williamsburg, Virginia.
Dimitri Rubin is senior director at CSR and is responsible for the development of the SiRFusion system. He has worked in the wireless communication field for 24 years.
Don Leimer is managing the GNSS Advanced Development group at CSR. Mr. Leimer has led and contributed to numerous commercial and military GNSS developments including GPS Phase I.
Greg Turetzky is senior director for location and technology strategy in CTO office at CSR. He has an M.S. in computer science from Johns Hopkins and holds a number of patents in GPS.
Murray Jarvis is a consultant research and development engineer at CSR. He holds a Ph.D. in physics and has worked on a variety of positioning technologies including GNSS, cellular and Wi-Fi.
October was a month of shows, rumors and announcements. Testing of competing indoor location positioning technologies is being planned by the FCC; prospects for some companies will ride on the public results. Apple may be turning to TomTom to save it from its mapping inaccuracy issues, dubbed Mapplegate. This month’s CTIA show was flat; attendees were wondering if it was the last chapter of the fall show. Interesting industry tidbits were heard at the MforMobile Location Business Summit. New Google Ad Word rates may be created that are also based on the distance between the handset and advertiser’s location. History can be harsh, remembering an unfortunate calculation by a location industry giant. Marketers continue to be frustrated by the mobile industry’s continued difficulty to completely measure ad results.
The FCC sees indoor location as a critical safety concern for E911 emergency response. The commission has tasked an advisory committee to evaluate indoor location positioning technologies. TechnoCom has been chosen to conduct the independent testing as a neutral third party. The test bed is in about 20 structures of various types, in locations that range from highly dense urban to sparse landscape. The following companies are submitting technology for the testing: Qualcomm (AGPS/AFLT/Cell ID), NextNav (GPS-like terrestrial beacons), Boeing (LEO satellites using the Iridium constellation), and Polaris (RF fingerprinting). Additional companies submitted technology, but later withdrew. Test results should be made public in March of 2013. A public workshop on this testing is being held at the FCC on October 24 and can be watched online at www.fcc.gov/live.
Indoor Mapping. At the Location Business Summit, it was clear that the retail and hospitality industries is anxious to start exploring indoor marketing based on real-time location. They seem to expect it will start out working flawlessly. It won’t. In addition to the indoor positioning being early stage, mapping quality is uneven. The gold bar of quality assurance for outdoor mapping is aerial fly-overs and street driving. In some situations crowd sourcing works. For indoor maps, it’s the Wild West. Currently there are no standards for vetting indoor mapping. Maps are being created of greatly varying quality, sometimes by way of rough diagrams found on the Internet that are then shoe-horned into the outlines of buildings.
TomTom to the Rescue? Shares in TomTom, maker of personal navigation devices (PNDs) and mapping, jumped to a three-week high on speculation that it may be taken private by its founders with the help of Apple. In turn, Apple could buy TomTom’s maps database to correct its mapping problems. TomTom’s founders own 47 percent of the company, but may be held back by the uptick in share value.
Paying for Location. Reportedly, Google has location-based AdWords in beta. Advertising rates go up the closer the targeted user is to the venue being promoted. A restaurant ad is more relevant, and more likely to draw a person who is one mile away than 20 miles. Some travelers will park near a string of hotels and use a site like hotels.com to find the most competitively priced room for that evening. An ad for a hotel on the other side of town is of lesser value and would be cheaper.
Comments Heard at the Location Business Summit by MforMobile this Month:
“We need to build ambient intelligence into devices. Nobody needs more information, more apps, ads, logins or devices. It isn’t sustainable.”
“Location data on the consumer side is often junky because phones are trying to conserve battery, and won’t invoke GPS.”
“You can get better locations from the carrier network, but it is too expensive a proposition for advertisers.”
“We find that hyper-local ad targeting leaves us with too few people to address.”
Can I Turn Back the Clock? In an interview for Forbes in 2003, Min Kao, CEO of Garmin, puts a stake in the ground. He says he does not seek to compete in navigation with the mobile phone, the likes of Nokia and Motorola, as that is the kind of commodity business Garmin would like to avoid. The PND vendors continue to be squeezed between the OEM embedded equipment and the smartphone. It is hard to be optimistic about the PND market, commented John Canali of Strategy Analytics at the Location Business Summit. Heavy discounting has led to plummeting revenues. “The PND companies are hardware focused in a market whose foundation is software. It will be very difficult to transform PND companies,” says Canali. “They will struggle.” In 2009, Google announced that all Android phones built on OS 1.6 or higher would have free turn-by-turn directions. Nokia followed shortly after. So it began.
A Little Slow. CTIA drew more than 5,000 people to attend MobileCon, its fall show with a new brand name. You may remember it as CTIA Enterprise and Applications. This was a significant decline from last year when 10,000 to 15,000 conference-goers attended. Activity was slow and the exhibit floor was smaller. Conference sessions were held on the exhibit floor.
Still Can’t Close the Loop. The industry continues to be unable to provide advertisers with metrics of how many pizzas a mobile ad sold. Papa John’s Pizza will know if someone has clicked to call or clicked to map, but Papa John’s won’t know if those actions resulted in a purchase. Without this fundamental metric, advertisers complain that it is hard to build a business case for mobile advertising. The click rates that they can track aren’t always representative because of user errors that include fat fingers, fraudulent clicks and pocket dialing.
The FCC sees indoor location as a critical safety concern for E911 emergency response. The commission has tasked an advisory committee to evaluate indoor location positioning technologies. A public workshop on this testing is being held at the FCC on Wednesday, October 24, and can be watched online at www.fcc.gov/live.
TechnoCom has been chosen to conduct the independent testing as a neutral third party. The test bed is in about 20 structures of various types, in locations that range from highly dense urban to sparse landscape. The following companies are submitting technology for the testing: Qualcomm (AGPS/AFLT/Cell ID), NextNav (GPS-like terrestrial beacons), Boeing (LEO satellites using the Iridium constellation), and Polaris (RF fingerprinting). Additional companies submitted technology, but later withdrew. Test results should be made public in March of 2013.
ByteLight, a provider of LED (light-emitting diode) based indoor positioning technology, announced that it has received $1.25 million in funding from individual and institutional investors, led by VantagePoint Capital Partners. ByteLight will use the funding to build its team, deploy at pilot locations, and expand its ecosystem of lighting partners.
Using ByteLight’s LED lighting-based indoor positioning solution, commercial and enterprise building owners, public safety officials, retail outlets and public spaces such as airports, museums and convention centers can target customized information, special offers and other data directly to users based on their precise location inside a building.
We are making history. The rate of iOS and Android device adoption has surpassed adoption rates for any other consumer technology in recent history, reports analytics firm Flurry. Android and iOS devices are being adopted at a rate 10 times faster than the rate of PC adoption during the 1980s. Smart device adoption is growing twice as fast as Internet adoption during the 1990s, and three times faster than that of recent social network adoption. Flurry estimates there were more than 640 million Android and iOS devices in use as of July 2012. The U.S., followed by China, has the most active iOS and Android devices. However, China had the fastest growth of active devices last year and its active user base will soon overtake the U.S. Other news this month includes security concerns with LBS offerings, developments in the indoor location market, voice navigation for bikes, and unusual election activities.
With cause, people are concerned about the security of location-based applications. In a poll focused on LBS security, a quarter of 1,000 Americans surveyed indicated both concerns about third-party use of personal information for marketing purposes and strangers knowing too much about personal activities. Surprisingly, about 20 percent indicated a concern for their actual personal safety. The poll was conducted by the non-profit security group, ISACA. Nearly one-third of consumers in ISACA’s survey use location-based apps more than they did a year ago.
It isn’t just LBS that carries security risks. Smartphones themselves are inherently vulnerable. “Every smartphone subscriber end-point is a potential threat to the mobile network and creates hundreds of millions of points of network vulnerability,” says Jeff Orr of ABI Research. Currently, protection is focused on hardware and end-user application security. To more ably face threats, defensive security measures will grow more sophisticated and encompass contextual information about usage, location, and user. Perversely, this is the same information sought by mobile advertisers. Today, carriers are focused on 4G roll-out and delivering the hottest handset, but they need to be just as concerned about security.
A Whiff of Hyperbole in the Indoors. The indoors location market is going to be big, but I think that ABI Research’s forecast of indoor maps and services reaching more than $2.5 billion by 2017 is overstated. I agree with their assertion that business models are changing with the most significant indoor mapping companies increasing their scope to include more revenue enhancing activities. These still focus on indoor location, but include application development, location technologies, analytics, and advertising.
Indoor Location Club. The In-Location Alliance has been formed by 22 companies, including Nokia, Qualcomm, and Samsung, to pursue high-accuracy indoor positioning and related services. One of their goals is to ensure a multi-vendor environment by promoting open interfaces and a standard-based approach. Members are encouraged to execute their own pilots and present their data to the Alliance. The primary solutions will be based on enhanced Bluetooth 4.0 low-energy technology and Wi-Fi standards using relevant existing or upcoming features of those technologies. Pre-commercial pilots and business model verifications will start in 2012, while 2013 is expected to bring mobile handset-based implementation, enabling the first consumer applications in the indoor mobile environment.
Enterprise GPS Doing Well Approximately 5.5 million GPS/wireless devices are used to manage fleet vehicles, trailers, construction equipment, and mobile workers, estimates C.J. Driscoll & Associates. By 2015, this market will expand to more than nine million units and annual hardware and service revenues will grow to over $3.0 billion, predicts Driscoll. Growth is expected to be strongest in the local GPS fleet tracking market, which is expanding at a rate of 15-20 percent per year.
Listen to Your Bike. Google has added turn-by-turn voice-guided navigation for bike riders in 10 Nordic and European bike loving countries. Bikers can either listen to the voice or view the route on a phone. In the U.S. and Canada, a beta version will be available. Google maps contain more than 330,000 miles of biking lines. These are color classified as either dedicated bike trails with no motor vehicles, streets with bike lanes, or other streets recommended for biking. Users can use Map Maker to add bike routes.
Election Coverage. You may have heard that a group called Crossroads GPS spent $5.3 million to run ads to defend Governor Romney’s proposed tax plan. Crossroads GPS is not a new faction of the LBS industry. Crossroads GPS (Grassroots Policy Strategies) is a conservative organization with an unlikely acronym.
Save the Date. I’ll be moderating a panel debate, “Opening up the Indoors for Location Services,” at MforMobile’s Location Business Summit 2012, being held in San Jose October 16-17. TheWhereBusiness and NFC Insight are now MforMobile.
