Quad-Constellation Receiver: GPS, GLONASS, Galileo, BeiDou

The implementation changes and first live tests of BeiDou and
Galileo on Teseo-3 GNSS chips developed in 2013 are covered,
bringing it to a four-constellation machine.  By 2020, we expect to
have four global constellations all on the same band, giving us
more than 100 satellites - under clear sky, as many as 30 or 40
simultaneously: Philip G. Mattos and Fabio Pisoni

As reported by GPS World: Multi-constellation GNSS first became widely available in 2010/2011, but only as two constellations, GPS+GLONASS. Although receivers at that time may have supported Galileo, there were no usable satellites. BeiDou was a name only, as without a spec (an interface control document, or ICD), no receivers could be built.

However, the hardware development time of receivers had been effectively shortened: the Galileo ICD had been available for years, BeiDou codes had been reverse-engineered by Grace Gao and colleagues at Stanford, and at the end of 2011 they were confirmed by the so-called test ICD, which allowed signal testing without yet releasing message characteristics or content.

The last weeks of 2012 saw two great leaps forward for GNSS. Galileo IOV3 and 4 started transmitting at the beginning of December, bringing the constellation to four and making positioning possible for about two hours a day. At the end of December, the Chinese issued the BeiDou ICD, allowing the final steps of message decode and ephemeris calculation to be added to systems that had been tracking BeiDou for many months, and thus supporting positioning. The Teseo-2 receiver from STMicroelectronics has been available for some years, so apart from software development, it was just waiting for Galileo satellites; however, for BeiDou it needed hardware support in the form of an additional RF front end. Additionally, while it could support all four constellations, it could not support BeiDou and GPS/Galileo at the same time, as without the BeiDou ICD the spreading codes had to be software-generated and used from a memory-based code generator, thus blocking the GPS/Galileo part of the machine.

The Teseo-3 receiver appeared late in 2013, returning to the optimum single-chip form factor: RF integrated with digital silicon and flash memory in the same package, enabling simultaneous use of BeiDou and GPS/Galileo signals. Multi-constellation in 2012 was GPS+GLONASS, which brought huge benefits in urban canyons with up to 20 visible satellites in an open sky. Now, for two hours a day in Europe while the Galileo IOVs are visible, we can run three constellations, and in the China region, GPS/BeiDou/Galileo is the preferred choice.

This article covers the first tracking of four Galileo satellites on December 4, 2012, first positioning with Galileo, and first positioning with BeiDou in January 2013. It will cover static and road tests of each constellation individually and together as a single positioning solution. Road tests in the United States/Europe will combine GPS/GLONASS/Galileo, while tests in the China region will combine GPS/Galileo/BeiDou. Results will be discussed from a technical point of view, while the market future of multi-constellation hardware will also be considered.

In the 2010–2020 timeframe, GLONASS and BeiDou (1602 MHz FDMA and 1561 MHz respectively) cost extra silicon in both RF and digital hardware, and cause marginal extra jamming vulnerability due to the 50 MHz bandwidth of the front end. The extra silicon also causes extra power consumption.

After 2020, GLONASS is expected to have the L1OC signal operational, CDMA on the GPS/Galileo frequency, and BeiDou is expected both to have expanded worldwide, and also to have the B3 signal fully operational, again on 1575 MHz. At that point we will have four global constellations all on the same band, giving us more than 100 satellites. With a clear sky, the user might expect to see more than 30, sometimes 40, satellites simultaneously.

Besides the performance benefits in terms of urban canyon availability and accuracy, this allows the receiver to be greatly simplified. While code generators will require great flexibility to generate any of the code families at will, the actual signal path will be greatly simplified: just one path in both RF (analog) and baseband (digital) processing, including all the notch filters, derotation, and so on. And this will greatly reduce the power consumption.

Will the market want to take the benefit in power consumption and silicon area, or will it prefer to reuse those resources by becoming dual-frequency, adding also the lower-L-band signals, initially L5/E5, but possibly also L2/L3/L6 ? The current view is that the consumer receiver will go no further than L5/E5, but that the hooks will be built-in to allow the same silicon to be used in professional receivers also, or in L2C implementations to take advantage of the earlier availability of a full constellation of GPS-L2C rather than GPS-L5.

This article presents both technical results of field trials of the quad-constellation receiver, and also the forward looking view of how receivers will grow through multi-frequency and shrink through the growing signal commonalities over this decade.

History

Galileo was put into the ST GPS/GNSS receiver hardware from 2006 to 2008, with a new RF and an FPGA-based baseband under the EU-funded GR-PosTer project. While a production baseband (Cartesio-plus) followed in high volume from 2009, in real life it was still plain GPS due to the absence of Galileo satellites.

The changed characteristics in Galileo that drove hardware upgrades are shown in Figure 1. The binary offset carrier BOC(1,1) modulation stretches the bandwidth, affecting the RF, while both the BOC and the memory codes affect the baseband silicon in the code-generator area.

Figure 1. Changes for Galileo.

Next was the return to strength of the GLONASS constellation, meaning receivers were actually needed before Galileo. However the different center frequency (1602 MHz), and the multi-channel nature of the FDMA meant more major changes to the hardware. As shown in Figure 2 in orange, a second mixer was added, with second IF path and A/D converter.

Figure 2. Teseo-2 RF hardware changes for GLONASS.

Figure 3. Teseo-2 and Teseo-3 baseband changes for GLONASS.

The baseband changes added a second pre-processing chain and configured all the acquisition channels and tracking channels to flexibly select either input chain. Less visible, the code-generators were modified to support 511 chip codes and 511kchips/sec rates.

Teseo-2 appeared with GPS/GLONASS support in 2010, and demonstrated the benefit of GNSS in urban canyons, as shown by the dilution of precision (DOP) plot for central London in Figure 4. The GPS-only receiver (in red) has frequent DOP excursions beyond limits, resulting either in bad accuracy or even interrupted fix availability. In contrast, the GNSS version (in blue) has a DOP generally below 1, with a single maximum of 1.4, and thus 100 percent availability. Tracking 16 satellites, even if many are via non-line-of-sight (NLOS) reflected paths, allows sophisticated elimination of distorted measurements but still continuous, and hence accurate, positioning.

Figure 4. DOP/accuracy benefits of GNSS.

BeiDou

Like Galileo, BeiDou is a story of chapters. Chapter 1 was no ICD, and running on a demo dual-RF architecture as per the schematic shown in Figure 5. Chapter 2 was the same hardware with the test ICD, so all satellites, but still no positioning. Chapter 3 was the full ICD giving positioning in January 2013 (Figure 6), then running on the real Teseo-3 silicon in September 2013, shown in Figure 7.

Figure 5. Demo Teseo-2 dual RF implementation of BeiDou.

Figure 6. Beidou positioning results.

Figure 7. Teseo 3 development board.

The Teseo-3 has an on-chip RF section capable of GPS, Galileo, GLONASS and BeiDou, so no external RF is needed.

The clear green space around the Teseo-3 chip in the photo and the four mounting holes are for the bolt-down socket used to hold chips during testing, while the chip shown is soldered directly to the board. Figure 8A shows the development board tracking eight BeiDou satellites visible from Taiwan.

However, the silicon is not designed to be single-constellation; it is designed to use all the satellites in the sky. Figure 8b shows another test using GPS and BeiDou satellites simultaneously.

Figure 8A. Beidou.

Figure 8b. GPS+Beidou.

A mobile demo on the Teseo-3 model is shown running GPS plus BeiDou in Figure 9, a road test in Taipei. Satellites (SV) up to 32 are GPS, those over 140 are BeiDou, in the status window shown: total 13 satellites in a high-rise city area, though many are non-LOS.

Figure 9. GPS + Beidou roadtrack in Taipei.

Extending the hardware to add BeiDou, which is on 1561 MHz and thus a third center frequency, meant adding another path through the IF stages of the on-chip radio. After the first mixer, GPS is at 4 MHz, and GLONASS at about 30 MHz, but BeiDou is at minus 10 MHz. While the IF strip in general is real, rather than complex (IQ), the output of the mixer and input to the first filter stage is complex, and thus can discriminate between positive frequencies (from the upper sideband) and negative ones (from the lower sideband), and this is normally used to give good image rejection. In the case of BeiDou, the filter input is modified to take the lower sideband, that is, negative frequencies, and a second mixer is not required; the IF filter is tuned to 10 MHz. The new blocks for BeiDou are shown in green in Figure 10. The baseband has no new blocks, but the code generator has been modified to generate the BeiDou codes (and, in fact, made flexible to generate many other code types and lengths). Two forms of Teseo-3 baseband are envisaged, the first being for low-cost, low-current continues to have two input paths, so must choose between GLONASS and BeiDou as required. A future high-end model may have an extra input processing path to allow use of BeiDou and GLONASS simultaneously.

Figure 10. Teseo-3 RF changes for Beidou shown in green.

Galileo Again

Maintaining the chronological sequence, Galileo gets a second chapter in three steps. In December 2012, it was possible for the first time to track four IOV satellites simultaneously, though not to position due to the absence of valid orbit data. In March 2012, it was possible for the first time to demonstrate live positioning, and this was done using Teseo-2 simultaneously by ESA at ESTEC and STMicro in Naples and Milan, our software development centres.

The demos were repeated in public for the press on July 24, 2013, at Fucino, Italy’s satellite earth station, with ESA/EC using the test user receiver (TUR) from Septentrio, and ST running simultaneous tests at its Italian labs. Figure 11 and Figure 12 show the position results for the data and pilot channels respectively, with independent LMS fixes. In real life, the fixes would be from a Kalman filter, and would be from a combined E1-B/E1-C channel, to take advantage of the better tracking on the pilot.

Figure 11. Galileo positioning, E1-B.

Figure 12. Galileo positioning, E1-C.

Good accuracy is not expected from Galileo at this stage. The four satellites, while orbited to give good common visibility, do not also give a good DOP; the full set of ground monitoring stations is not yet implemented and cannot be well calibrated with such a small constellation. Finally, the ionospheric correction data is not yet available. Despite these problems, the residuals on the solutions, against a known fixed position for the rooftop antenna, are very respectable, shown in Figure 13.

Figure 13. Galileo residuals, L1-B.

The common mode value is unimportant, representing only an offset in the receiver clock, and 10 meters is about 30 nanoseconds. The accuracy indicator is the spread between satellites, which is very respectable for a code-only receiver without full iono correction, especially around 640 on the TOW scale, where it is less than 2 meters. The rapid and major variation on the green data around t=400 is considered to be multipath, as the roof antenna is not ideally positioned with respect to other machinery and equipment also installed on the roof.

QZSS and GPS-III/L1C

Teseo-2 has supported the legacy (C/A code) signal on QZSS for some time, but Teseo-3 has been upgraded to handle the GPS-III/L1-C signal, waiting for modernized GPS. This signal is already available on the QZSS satellite, allowing tests with real signals. Significant changes were required in the baseband hardware, as the spreading code is a Weill code, whose generation complexity is such that it is generated once when the satellite is selected, then replayed real time from memory. Additionally it is long, in two domains. It is 10230 chips — that is, long to store but also long in time, with a 10-millisecond epoch. On Teseo-3, the legacy C/A code is used to determine code-phase and frequency before handing over to the Weill code for tracking.

Using a long-range crystal ball and looking far into the future, a model of the future Teseo-4 DSP hardware is available, with 64 correlation taps per satellite. Running this on the captured QZSS L1-C signal gives the correlation response shown in Figure 14. Having multiple taps removes all ambiguity from the BOC signal, simultaneously removing data transitions, which can alternatively be pre-stripped using the known pilot secondary code (which on GPS III is 5 dB stronger than the data signal). The resultant plot represents 2,000 epochs, each of 10 milliseconds, plotted in blue, with integrated result for the full 20 seconds shown in the black dashed line. Assuming vehicle dynamics is taken out using carrier Doppler, this allows extremely precise measurement of the code phase, or analysis of any multipath in order to remove it. This RF data was captured on a benign site with a static antenna, so it shows little distortion.

Figure 14. L1-C tracking on QZSS satellite.

Figure 15. Dual RF implementation of dual-band front end.

The Future

Having already built in extreme flexibility to the code generators to support all known signals and generalized likely future ones, the main step for the future is to support multiple frequencies, starting with adding L5 and/or L2, but as before, ensuring that enough flexibility is built in to allow any rational user/customer choice. It is not viable for us to make silicon for low-volume combinations, nor to divide the overall market over different chips. Thus our mainstream chip must also support the lower volume options.

We cannot, however, impose silicon area or power consumption penalties on the high-volume customer, or he will not buy our product.

Thus, our solution to multi-frequency is to make an RF that can support either band switchably, with the high band integrated on the volume single-chip GNSS. Customers who also need the low band can then add a second RF of identical design externally, connected to the expansion port on the baseband, which has always existed for diagnostic purposes, and was how BeiDou was demonstrated on T2. By being an RF of identical design to the internal one, it incurs no extra design effort, and would probably be produced anyway as a test chip during the development of the integrated single-chip version. Without this approach, the low volume of sales of a dual-band radio, or a low-band radio, would never repay its development costs.

Conclusions

All four constellations have been demonstrated with live satellite signals on Teseo-2, a high-volume production chip for several years, and on Teseo-3 including use in combinations as a single multi-constellation positioning solution. With the advent of Teseo-3, with optimized BeiDou processing and hardware support for GPS-3/L1C, a long-term single-chip solution is offered.

For the future, dual-frequency solutions are in the pipeline, allowing full advantage of carrier phase, and research into moving precise point positioning and real-time kinematic into the automotive market for fields such as advanced driver-assistance systems.

Acknowledgments

Teseo III design and development is supported by the  European Commission HIMALAYA FP-7 project.

This article is based on a technical paper first presented at ION-GNSS+ 2013 in Nashville, Tennessee.

ST GPS products, chipsets and software, baseband and RF are developed by a distributed team in: Bristol, UK (system R&D, software R&D; Milan, Italy (Silicon implementation, algorithm modelling and verification); Naples, Italy (software implementation and validation); Catania, Sicily, Italy (Galileo software, RF design and production); Noida, India (verification and FPGA). The contribution of all these teams is gratefully acknowledged.

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CES 2014: Intel Abandons Smartphones, Focuses On Wearable Computing And Tablets

As reported by Extreme Tech: Intel has delivered its keynote at CES 2014, and rather refreshingly the presentation focused almost entirely on wearable and perceptual computing. 

After years of struggling with the ultrabook moniker and trying to squeeze its way into the smartphone market, it seems Intel is finally ready to lead from the front and create new markets, rather than milk existing markets dry. It’s far from confirmed, but we would not be surprised if this was the end of Intel’s smartphone aspirations. With Intel’s launch of Dual OS devices that run Android and Windows on the same chip, it hasn’t given up on mobile entirely — but there’s still a very long road ahead of Intel if it wants to break into the tablet market in a significant way.

Wearables, wearables, wearables

Back in September 2013, Intel surprised us by showing off Quark — a small, low-power core that’s designed to be produced cheaply at foundries like TSMC, much like an ARM core. At CES 2014, Intel is now showing off a range of gadgets and wearable devices — reference designs, not final products — that appear to be powered by the same Quark processor.

The first device was an earpiece called Jarvis (pictured right), which is worn on the ear like a Bluetooth headset. The idea is that Jarvis is always-listening, allowing you to issue Siri-like commands at any time — save an appointment in your calendar, phone a friend, etc. 

Like other wearable computers, Jarvis itself is fairly dumb; for most of its capabilities, it bonds with an Android smartphone via Bluetooth. Sadly, we’re not yet at the point where headsets — a class of devices that includes Google Glass — have the battery power to perform complex calculations and remain permanently connected via Wi-Fi or GSM/LTE.

Next up was a smartwatch prototype, which apparently doesn't need to be tethered to a smartphone, and has built-in GPS, so that it can be used for geofencing (good for keeping track of your wandering schoolkids and spouse). If this has built-in cellular connectivity (which is implied by the lack of tethering), this could be a very exciting device indeed. 

Intel also demonstrated some smart earbuds that monitor your heart-rate, while being powered via your device’s headphone jack. For charging Jarvis (and perhaps the smartwatch too), Intel showed off a smart charging bowl — which presumably uses wireless inductive charging to conveniently recharge your devices at the end of the day. All of these devices are reference designs/prototypes, but CEO Brian Krzanich made it sound like Intel has some partners that will bring these devices to market.

Making everything smartMuch more interesting than vaguely useful wearables, though, Intel’s Krzanich also unveiled Edison — an SD card form factor computer. ”It’s a full Pentium-class PC in the form factor of an SD card,” Krzanich said. Inside the SD card is a dual-core 22nm Quark processor, RAM, flash storage, WiFi and Bluetooth radios, and a microcontroller for real-time I/O with external devices. Edison currently runs Linux, but Intel didn't give any further guidance on OS support.

The idea behind Edison is to make everything smart. As long as a device has an SD card slot and some kind of power source, you could theoretically use Edison to turn it into a smart device. On stage at CES 2014, Intel showed off the “smart turtle” baby monitoring system — a monitor, powered by Edison, that clips to a baby’s clothing and keeps track of its heart rate, breathing, and movements. Edison then transmits these details to a smart mug, which gives the parent/babysitter constant status updates.

Intel’s “smart turtle” Nursery 2.0 baby monitor and smart mug, powered by Edison

Edison is clearly a good choice for rapid prototyping and fun DIY projects, but Intel is probably hoping that Edison becomes the platform of choice for a whole host of commercialized smart devices.

Intel also discussed perceptual computing at its CES 2014 keynote, including the RealSense dual-camera depth and gesture sensor, but it was mostly a repeat of what had already been covered at IDF 2013.

Intel’s first-gen Medfield smartphone. We hardly knew ye!

RIP Intel smartphones
To be honest, after being so horrendously late to the party, Intel’s success in the smartphone market was always an outside bet. While Intel’s upcoming Merrifield platform will finally feature a CPU (dual-core Silvermont), GPU (PowerVR 6), and modem (LTE) that can compete with Qualcomm, it’s probably a case of too little too late. Qualcomm, ever since it released the first SoC with integrated multimode LTE modem at the start of 2012, has had the smartphone market all stitched up.

Intel's CEO Brian Krzanich with a Dual OS laptop.

There is still some hope for Intel and other modem-latecomers (such as Nvidia) in the tablet market, though. 

The Android tablet market, for example, is set to grow a lot in 2014, and Intel’s Bay Trail is well placed to pick up a number of significant design wins. Intel also unveiled Dual OS at CES 2014, a technology that allows Intel-powered computers (laptops and tablets) to switch between Android and Windows. 

This is slightly more graceful than existing dual-OS hybrids, such as the dual-CPU Transformer Book Trio. Don’t expect Dual OS to be Intel’s next ultrabook-like marketing drive, though — Intel hasn't yet said whether Microsoft is on-board with the idea, and, rather ominously for CES, it didn't wheel a dozen Dual OS design wins onto the stage.

All in all, Intel’s CES 2014 presentation was very strong, and it makes me feel fairly optimistic for the future. After a couple of years of ultrabooks and smartphones, it’s refreshing to see Intel focusing on new and developing markets, rather than trying to milk every last penny out of inveterate (server, laptop) and quickly maturing (smartphone) markets.

Operator Safety in Utility Fleets

Driver safety is a concern among utility business owners and fleet managers. Often, the most dangerous part of the day for a worker in the utility industry is the time spent behind the wheel of the vehicle. The Bureau of Labor Statistics (BLS) reports that motor vehicle crashes are a leading cause of fatalities in the workplace-more than fires, explosions, falls, trips and equipment incidents combined. In addition, vehicle crashes occur every 5 seconds in the United States, according to the Occupational Health and Safety Administration (OSHA).

Vehicle crashes not only endanger the lives of your employees and others on the road, but they can also cause considerable financial strain on your company. Many of these incidents occur during the workday, during the commute to and from job sites-and employers bear the cost of these injuries that occur both on and off the job. The average cost of a crash costs an employer $16,500 and crashes involving injuries cost $74,000. If a fatality is involved, the cost increases to over $500,000, according to OSHA.

As a whole, motor vehicle crashes cost employers $60 billion annually in medical care, legal expenses, property damages and lost productivity. In addition, they drive up the cost of benefits such as workers' compensation, Social Security, and private health and disability insurance.

Many utility companies may use or consider using a global positioning system (GPS) fleet management solution for tracking and routing vehicles, but you may not realize fleet management solutions can also be used to monitor driver behavior and increase driver safety in many ways.

Educate Your Drivers
Many of the commercial vehicle crashes that occur throughout the year are preventable if your company implements a driver safety policy and gives your employees the tools to do their job safely, without negatively affecting productivity.

The first step to ensure your drivers practice appropriate driving behaviors and are safe on the road is to create safe driver policies and stick to policy enforcement. This should also be done in coordination with some type of driver behavior program. When considering a GPS fleet management solution for your company, you should find one that supports your business' strategy to address driver education and driver safety issues.

This can be accomplished with driver education courses that support your comprehensive strategy to promote safe driving habits. Online education courses provide safety managers and business owners a way to constructively engage and coach drivers to be safe behind the wheel. Courses may be offered from the GPS fleet management solution and can offer insight into aggressive, distracted, fuel-efficient or proactive defensive driving.

By addressing these behaviors proactively, fleet owners and safety managers can reduce driving incidents while also demonstrating the value of driver and fleet safety to employees, both experienced and novice. Promoting responsible driving habits from the start allows businesses to reduce insurance costs, cut down on potential collisions and decrease legal expenses. With the high number of driving incidents occurring each year, utility companies need to take a preventative approach to driver safety. Find a fleet management solution that gives you an outlet for your business to encourage responsible driving and ensure your fleet is operating at the safest level possible. When it comes to driver safety, prevention is the best policy.

Reduce Distracted Driving Opportunities
Distracted driving incidents are increasingly in the news, and for good reason. Distracted driving is a factor in 25 to 30 percent of all traffic crashes, according to OSHA. Drivers in the utility industry are often driving to and from sites, spending a great deal of time operating a vehicle. With busy schedules, road construction and other delays that occur, many employees feel pressured to multi-task to keep up with work-related responsibilities if they're driving. Drivers make more than 200 decisions during every mile traveled, increasing the chance that if your employee is distracted during his or her route, an incident may occur.

Currently, 41 states ban text messaging while driving. In addition, 11 states also prohibit hand-held cell-phone use while driving, which includes talking on the phone. In 2011, commercial truck and bus operators were also banned from all hand-held cell-phone use, except for emergency purposes. Since it is now illegal in most cases for your employee to use his or her phone while driving, the basic features of your GPS fleet management solution-tracking, routing, dispatching-are essential for any business.

Internal policies regarding use of private communication devices as well as fleet management systems can also provide additional distracted driving support, helping companies eliminate the need to communicate through a hand-held device. Make sure your GPS management solution provides an option for your company to discourage distracted driving by blocking or restricting calls, texts, emails, web browsing and more while the vehicle is being operated. Twenty-eight percent of all accidents are caused by mobile devices, increasing the importance to eliminate the risk of hand-held devices present.

Some of these distracted driving solutions allow your company to maintain your policies concerning mobile device use in vehicles, ensuring driver safety and protecting your company reputation. Some solutions also provide the option to set up an automatic Short Message Service (SMS) response to anyone who attempts to contact the driver on their cell-phone while he or she is driving, informing them the employee is driving and will contact them shortly. This eliminates the urge to multi-task because your employee knows the person attempting to reach them is aware they are unavailable while driving.

Cell phone use by drivers creates a serious threat for your company. According to the Network for Employers for Traffic Safety (NETS), more than 90 percent of all motor vehicle crashes are caused by human error and neglect. The risk of being the target of a lawsuit greatly increases when an on-the-job employee causes the vehicle crash.

By implementing a system that disables distracted driving, a utility company decreases communications to the basic, necessary interactions and greatly decreases the risk of an accident occurring.

Identifying Dangerous Driving
Despite designing company policies and creating a culture of safety, chances are there will still be an occurrence of distracted or aggressive driving in your company's fleet. The National Highway Traffic Safety Administration (NHTSA) defines aggressive driving as occurring when "an individual commits a combination of moving traffic offenses so as to endanger other persons or property," and includes but not limited to tailgating, weaving in and out of traffic, speeding, running stop signs or red lights and preventing other from passing. Aggressive driving actions were reported in 56 percent of fatal crashes from 2003 to 2007, with excessive speeding being the number one factor.

GPS fleet management solutions can monitor, measure and identify dangerous actions such as hard braking, quick acceleration, sharp turning and excessive speeding. This information is not used to scold employees, but to help drivers realize and identify any dangerous habits. Business fleet managers are supplied with concrete metrics to help identify risky drivers and work with their employees to take proactive actions against vehicle crashes.

Driver behavior information also helps in cutting down on excessive fuel costs, vehicle wear and tear, and additional expenses from insurance or potential collisions.

Importance of Driver Safety
Companies spend money on creating logos and company information to transform vehicles into moving billboards. Inappropriate or dangerous driving on the road in your fleets can turn that investment into a poor company image. Safety and compliance are major concerns for fleet managers, so it is important to have driver safety education and monitoring options in your overall fleet management solution.

Ultimately, it is your company's responsibility to protect your employees and company's image against the dangers of driving. Fleet management solutions can not only increase productivity and efficiency and decrease fuel usage, but assists fleet managers in working with employees and drivers to ensure everyone's safety on the road

Vehicle Navigation Systems Stay Relevant By Including Integrated DashCams

As reported by Engadget: Dedicated GPS units may be less popular these days, but Magellan has figured out a way to justify their existence: strap a dash camera to the back. The company's upcoming RoadMate 6230T-LM DashCam can both guide you through unfamiliar areas and record video to an SD card, saving you the trouble of mounting two devices in your car. 

Magellan's hybrid design is also handy even if you don't need directions, since you can watch live video from either the built-in camera or an optional wireless backup cam. The new RoadMate won't ship until April, but it will also cost $230 -- a relative bargain next to purpose-built dash cams that offer many of the same features.

iBeacon Location-Sensing Tech Put To Use At Grocery Stores

InMarket debuts its iBeacon platform in dozens of Safeway and
Giant Eagle supermarkets to give shoppers grocery list reminders,
deals, and reward points.

Apple's iBeacon location-sensing technology appears to be having a major breakthrough. Mobile shopping startup InMarket announced Monday that it's beginning to use the platform in more than 150 grocery stores across the US, according to The Associated Press.

This means the 20 million people who use InMarket's apps on its Mobile to Mortar platform will be able to get grocery list reminders, deals, and reward points at supermarkets like Safeway and Giant Eagle. To use the technology, shoppers have to opt in by downloading specific apps, like InMarket's Checkpoints.

Apple debuted iBeacon late last year on devices running iOS 7. The location-sensing technology works by sending off short-range (Bluetooth) transitions that notify mobile devices when they are within 100 feet of a beacon. This type of location-sensing technology can be used for indoor navigation, automatic ticketing, and location-relevant promotions.

iBeacon has already been used at Apple retail stores, is in testing mode with MLB at certain baseball stadiums, and will even be used for a scavenger hunt at this week's Consumer Electronics Show. Starbucks, Macy's, and American Airlines are also said to be testing the technology.

InMarket's iBeacon feature will be in more than 150 stores in Seattle, San Francisco, and Cleveland within the next two weeks; and the company plans to expand to thousands of grocery and retail stores by the end of 2014, according to the AP.

How Google Cracked House Number Identification in Street View

As reported by MIT Technology Review: But the task of spotting and identifying these numbers is hugely time-consuming. Google’s street view cameras have recorded hundreds of millions of panoramic images that together contain tens of millions of house numbers. The task of searching these images manually to spot and identify the numbers is not one anybody could approach with relish.

So, naturally, Google has solved the problem by automating it. And today, Ian Goodfellow and pals at the company reveal how they've done it. Their method turns out to rely on a neural network that contains 11 levels of neurons that they have trained to spot numbers in images.

To start off with, Goodfellow and co place some limits on the task at hand to keep it as simple as possible. For example, they assume that the building number has already been spotted and the image cropped so that the number is at least one-third the width of the resulting frame. They also assume that the number is no more than five digits long, a reasonable assumption in most parts of the world.

But the team does not divide the number into single digits, as many other groups have done. Their approach is to localize the entire number within the cropped image and to identify it in one go—all with a single neural network.

They train this net using images drawn from a publicly available data set of number images known as the Street View House Numbers data set. This contains some 200,000 numbers taken by Google’s Street View cameras and made publicly available. The training takes about six days to complete, they say.

Goodfellow and co say there is no point in using an automated system that cannot match or beat the performance of human operators who can generally spot numbers accurately 98 percent of the time. So this is the team’s goal.

However, that doesn't mean spotting 98 percent of the numbers in 100 percent of the images. Instead, Goodfellow and co say it is acceptable to spot 98 percent of the numbers in a certain subset of images, which in this case turn out to cover around 95 percent of the total.

But even this is significantly better than any other team has been able to achieve. “Worldwide, we automatically detected and transcribed close to 100 million physical street numbers at [human] operator level accuracy,” they say, describing this as an “unprecedented success.”

And they can do it at considerable speed. “We can transcribe all the views we have of street numbers in France in less than an hour using our Google infrastructure,” they say. Yep, that’s just one hour.

One interesting question is whether the same technique might help extract other numbers such as telephone numbers on business signs or even number plates.

However, Goodfellow and co are not optimistic. They say the success of their technique rests heavily on the assumption that street numbers are never more than five digits long. “For large [numbers of digits] our method is unlikely to scale well,” they say.

And of course, the system is not yet perfect. That 2 percent of misidentified numbers is still a thorn in the team’s side.

But in the meantime, Google can rest assured that it has made a significant step forward in character extraction and recognition: the localization and identification of numbers by a single neural network.

The big question of course is what’s next. And Goodfellow and co oblige by opening the kimono just a fraction: “This approach of using a single neural network as an entire end-to-end system could be applicable to other problems such as general text transcription or speech recognition.” 

Three CubeSats Released by the ISS

As provided by NASA: Cubes are orbiting the Earth. 

Measuring ten-centimeters on a side, CubeSats -- each roughly the size of a large coffee mug -- are designed to be inexpensive both to build and to launch. 

Pictured here, three CubeSats were released from the International Space Station (ISS) last November by the arm of the Japanese Kibo Laboratory module.  

CubeSats are frequently created by students as part of university science or engineering projects and include missions such as collecting wide angle imagery of the Earth, testing orbital radio communications, monitoring the Earth's magnetic field, and exploring the Earth's surrounding radiation. 

Depending on the exact height of their release, CubeSats will re-enter the Earth's atmosphere on the time scale of months to years.