FAQ

GPS is unsuitable for mass tracking of cars, necessary for an effective road pricing scheme. Such schemes have been touted for years as the answer to congestion by many countries. GPS has been around for years, but never used in this context, for many reasons as below:

Power: GPS draws high power to ‘hear’ satellites & process orbit calculations. GPS often runs phones flat quickly with constant location use. Congestion tracking can’t have high-power consumption. Devices are expected to operate self-powered for years. Hard-wiring power means retrofitting millions of vehicles at untenable expense, and can be easily defeated by severing power lines. Mass adoption requires secure self-contained power, like current (legacy) toll transponders mounted on windscreens.

Note: Security tracking is very different to congestion tracking. For security, the device may detect & transmit positions each ten minutes to be effective for its security purpose. Road pricing needs a much higher resolution tracking (billing by km), which consumes far more power than a GPS theft tracker.

ALSO: You can't ask for a low power GPS point, sort of in the same way you can't be half pregnant! Somethings need to be either yes or no. There is a fixed power cost to request and compute a single GPS location. NeoMatrix technology can be fully power scaled down progressively, so reducing power used (polling sampling rates, or sensor accuracy, AI processing) is easy, and only affects the positional error. GPS has no way to easily 'allow' greater error by reducing power used.

Antenna: GPS tracking requires an antenna mounted with line-of-sight to the sky. They mount inside the dashboard or intrusively on windscreens to hear signals. Antennas are an Achilles heel. Drivers can sever the antenna wire, or shield with foil to make the vehicle appear not moving, and thus will not incur congestion road use fees. Even if movement itself is detected via sensors, lack of GPS positions means movement is assumed non-main road use, such as on private property or local roads, so not billed.

Heavy earthmoving equipment can’t use GPS easily due to difficulty placing sensitive antennas. Thieves break antennas or wires to steal vehicles, as GPS antennas can’t be fitted easily or securely internally in a solid metal vehicle due to faint signals being blocked. Such vehicles use wireless or GSM tracking instead, which isn’t as good for position accuracy and has coverage limitations, but is fitted securely.

Retrofit: Positioning technology requiring an external power supply to provide constant power, or a GPS antenna that must be carefully positioned with line-of-sight to sky (e.g. under dashboard, not under the hood) is wholly unsuitable for mass adoption of secure road pricing system. The cost of retrofitting millions of vehicles with expensive tracking hardware would be immense, and also incur liability risks.

It would cause uproar that governments are installing surveillance equipment into vehicles. Drivers will be most unhappy having their vehicles intrusively modified. By being so physically installed, it’s a ‘bigger thing’ than simply placing a small toll transponder on their windscreen and never worrying about it again.

Communication: GPS is point based tracking, requiring several Kb of data to transmit routes. Dynamic road pricing requires high resolution of positions recorded and sent, unlike normal security asset monitoring. They need a solid internal power source. Neomatrix compresses routes so small they can be powered externally (no battery) via RFID like current toll transponders to send a full route history. Neomatrix compresses routes to a few dozen bytes, not several Kb (two orders of magnitude smaller).

For reference, similar new tracking technology Sigfox (Still antenna based) reports: An uplink message has up to 12-bytes payload & takes an average 2s to transmit to the network. This is sufficient to send 2x GPS points at 3m accuracy. By comparison, Neomatrix can often send a 30min full route in just 20 bytes!

Security: GPS systems are defeated easily, with lots of internet examples. It’s semi-common practice among some commercial drivers to disable tracking of vehicles or their containers to avoid monitoring. With the need for an ‘accessible’ antenna and power cable, such devices can be very defeated by severing wires, shielding or damaging antennas, or using (illegal) GPS jamming devices which are very cheap, and used regularly. This causes problems - even drone crashes.

At extremes, it’s easy to disable GPS satellites by rouge nations firing ASAT rockets to disrupt economies. GPS Spoofing can also affect wide areas, reported by the BBC as used in Russia. Even solar storms can take out GPS.

While unlikely, the more we rely on GPS, it becomes a weak link target. GPS has a place in many contexts, but vulnerabilities in GPS mean it’s not viable for road pricing, when used in millions of cars, and many countries are seeking alternatives to GPS for security, and due to its shortcomings.

Cost: With millions of vehicles, GPS at scale is expensive, let alone significant installation costs and associated liability. GPS is cheap individually, but not compared to alternative positioning technology such as from Neomatrix which is far cheaper, simpler, and needs no antenna or installation.

Privacy: GPS is not privacy friendly. See next FAQ section

Privacy: GPS resolves position to an error of maybe 3m, so it is high-resolution tracking. It is an obvious concern for drivers, who feel this is intrusive. The purpose of tracking is solely to detect and price use of main roads at busy and/or congested times, yet the government is tracking their movements everywhere, anytime, and accurately. It seems an extreme overreach.

The government may say ‘Yes we could track you in private areas, but we promise we won’t do this’ would be endless debate and concern in consumer’s minds that they are entering an Orwellian surveillance state. Drivers don’t want to be tracked when having affairs, spending their work time at the beach, or perhaps even speeding on quiet roads. Even when conducting business normally, drivers will be ‘disconcerted’ knowing they are tracked to such high resolution all the time.

Alternative, newer technology addresses privacy in novel ways, with technology that is ‘physically incapable’ of tracking movement, except on main roads, and at known/defined congested peak hour times which is the purpose of the data capture. Drivers will accept privacy implications far better if it’s limited to only the purpose designed, which is a core GDPR data privacy requirement too.

As a thought experiment, the government could easily erect many toll booths across all main roads to implement large scale dynamic road pricing. However, erecting toll booths each km along main roads is cost prohibitive, and visually unsightly. Still, this would not invoke extreme privacy concerns that GPS would. Tracking ‘on’ the car or person is vastly more intrusive than a fixed toll booth tracking a car passing by. Users easily understand the reason for the toll booth tracking, but can’t justify individual car tracking constantly ‘in case’ it may drive along a toll road at some future time.

To address privacy well, monitoring systems should only track cars when actually driving busy main roads, but not to the high resolution of GPS, or to the global coverage area of GPS (everywhere).

Neomatrix positioning can only do main road ‘route tracking’, not point tracking (like GPS), so allows privacy to be addressed by default – as it is only able to monitor movement along main road routes.

Evidence on privacy concerns: A significant UK Government paper called London stalling. Reducing traffic congestion in London includes these comments from David Kurten AM, UKIP Group Lead on the Transport Committee: “The ultimate aspiration for London however is ‘big brother’ style total vehicle monitoring for the entire Greater London area. All vehicle movements would be monitored and charged by a government agency: probably TfL. This will destroy privacy & civil liberties for motorists in London.”

Comments above show an (incorrect) understanding that vehicle monitoring must be ‘all vehicle movements’, meaning point based (GPS). Route based tracking is very different, and almost an extension on more toll roads, but without needing any toll gantries.

Privacy is addressed by a radical shift in how we monitor cars. Existing tracking systems are ‘Big Brother’ and cover ‘entire areas’, when this isn’t needed if a new system can only physically monitor main road driving. Route tracking is also technically unable to identify end points of journeys, as they are not ‘a route’, being another benefit for privacy over GPS which has no difficulty knowing exact end addresses.

Many examples of major privacy debates on road tolling exist, such as www.notolls.org.uk/#reasons and www.driversalliance.org.uk and https://en.wikipedia.org/wiki/Road_pricing_in_the_United_Kingdom#Privacy

Any location tracking is highly intrusive, and rightly carries a laser focus in GDPR and other legislative protections. Tracking can offer massive benefits to society in safety, and in efficiency. It can also be creepy and intrusive. Much debate has been around Apple Airtag, though this is just a more well known and cheaper tech, of what has already been available for years anyway.

NeoMatrix tracking can rival GPS, but has THREE major Privacy safeguards that differ from GPS.

For context, please understand and note the Android/iOS permissions that allow you to share your approximate location vs your precise. Most of us don't care about anyone knowing approximate, but precise location is very different, which is why there is a specific permission on all smartphones to control this 'location precision'.

LESS REAL TIME

GPS resolves high precision location points, in real time. NeoMatrix can offer some limited ability like this, but more so on main roads. Because a critical aspect of our technology requires forward movement to resolve historical accuracy. The more you drive on, the more accurate we can resolve your past locations as we have more data for the AI to assess. Think of it like the more GPS satellites your phone can see, the more precise your location. We need to 'drive on' to see more signal data.

This is perfect for many use cases that do not require 'live' blinking red dot locations showing where you are RIGHT NOW! This natural phenomena provides privacy protection around the issue of location and time precision.

DESTINATION ACCURACY

GPS has a relatively fixed accuracy. NeoMatrix uses an entirely different method to locate, which is far more accurate on main roads, compared to destinations. The AI uses many signals to resolve position, but the noise is naturally far greater in local roads, which are far more likely to be destinations, and more likely residential destinations. Because in general, all movement follows a hump. The trip usually starts on small roads, transitions up to more and more main roads, then down again to local roads. Not always, but usually. Also, most travel time is spent on main roads, and at higher speeds where speed and signal to noise ratio of sensors is relevant, and so on.

For may technical reasons, there is a lot more 'noise' in the area of local roads, such that position accuracy with GPS is generally always high precision, where NeoMatrix is high precision on MAIN roads, but more approximate in local roads, or at least not always as precise. So while it's not perfect, and hard to understand - there are natural, mathematical phenomena that is indirectly preserving privacy. It's a bit like magic privacy protections for smart road pricing. We can accurately track main road use, but are technically unable to be as accurate in local road destinations on average. Sometimes we will, but in general it's far less. Like saying 'give me privacy where I want it (home or work address / approximate location) but less where I don't really care as much (main roads during a route / precision location).

GEOFENCE PRIVACY

GPS always provides precision. A system could elect to 'mask' the precision, like a smartphone OS hiding precise locations, and only allowing approximate locations through. However, the hardware level always captures the precise position. Smart folk can always hack hardware to bypass the obfuscation of precise location once it is captured. So too, any software which claims to do so may not actually do so. There is always trust in any system that says 'we don't do bad things with your private data'. We rely on insider whistleblowers or audits or other things to detect bad actors, but otherwise how would you know!

With GPS, you COULD design a system to geofence say, all main roads. And only 'allow' main road tracking data to be provided, such as for the provision of dynamic road pricing. This would be 'a way' to obscure destination addresses, as unless they are ON the main roads which have tolling attached, they are out of bounds. Promise. We won't lie to you. Really?!

NeoMatrix works very differently. Our AI works to reference datasets, which is sort of like a hugely reprocessed geospatial database but in a different format. Trilateration signals from GPS satellites are raw, and can always be used to determine precise positions, but not so NeoMatrix. The reference data used by the system can be geofenced, AND the device can be configured to be limited in sending, such that it's possible to cryptographically prove that a tracking device can't 'track' outside it's allowed geofenced area. It can't determine position. So we are not artificially limiting the sending of unauthorised positions, we are designing a privacy failsafe system that prevents such locations from being detected. They are off the map, because the system needs a sort of AI map, which can be configured to ONLY include authorised locations.

By allowing white hat hackers to audit the system, and to observe the communication of tracking devices, it's easy to demonstrate the system is ONLY able to see and report allowed locations. So for a toll road solution, this is magic. It allows road providers to directly bill for road use by time of day and distance, while specifically NOT allowing anyone to see locations outside 'the system' as so configured. Even law enforcement can't subpoena records, as the position data in question isn't ever generated, let alone stored. This requires also that there is no 'raw' sensor data cached on devices, as this would facilitate path reconstruction via AI models that do not have the geofence limitations. But this is very easy to design.

In a nuclear reactor, you want to design FAILSAFE. Where human error, hurricanes, Russian missiles and cyber attacks are all completely unable to cause a meltdown, as we fail SAFE. A train driver having a heart attack will stop responding to the system prompts, and thus the train will safely stop. So too, NeoMatrix allows a failsafe privacy in ways that GPS simply can't possibly do with any confidence, due to the nature of the technology.

For more on NeoMatrix Privacy, see these links:

GPS: NOT Privacy Friendly (Road Congestion Pricing)

GPS: Speeding Privacy

Opening Debate: New User Privacy Settings

Legislation needed: New privacy controls
Tracking devices: User concerns

Proposed Global Solutions to tracking privacy

And more!

GPS is a point tracking system and provides high accuracy, high resolution data on vehicle speed. This is frequently used by fleet managers and parents to take action against offenders.

For mass adoption of a road pricing scheme, the new ability of authorities to instantly detect all instances of speeding with accuracy is a worrying concern for big brother. Speeding isn't a factor in causing road congestion, and indeed while illegal, it could even be seen as helpful for reducing time spent on roads. Strategies to reduce congestion should not be confused with, or integrated with initiatives to address speeding.

With the public sensitive to big brother privacy, 'mass surveillance' of citizens for purposes of reducing congestion - such systems need to take great care they don't bleed into areas they were not originally designed for.

Because Neomatrix isn't a point based tracking system, it simply can't be used for this in the same way as GPS. It can't reliably detect isolated instances of speeding. Additionally, it can't detect low level speeding in metro areas. The monitoring method simply can't 'see' these events clearly. Only prolonged speeding can be detected, exactly how point-to-point speeding cameras work. The public seem more comfortable with these schemes than being caught at a specific 'point', and want the ability to e.g. speed in order to overtake, but not necessarily have this detected as an offence.

The Neomatrix positioning technology can't detect speeding easily unless prolonged, but also, the NeoTag format smooths out speeding as part of its compression method. The data received from smart number plates by road authorities is thus even more broad, with individual and isolated speeding not seen clearly to begin, and also further smoothed if it is detected.

The end result is that unlike a point tracking system like GPS, Neomatrix positioning directly addresses privacy concerns on speeding detection. The system can be used to detect speeding but only in limited cases of extensive or prolonged speeding, and is far less likely to detect speeding in metro areas due to the smoothing methods. The public may be more accepting of this use case, but essentially, the system is designed to reduce traffic congestion, not to be used as a big brother surveillance tool, such as mass speeding detection. That it can't be used effectively for such surveillance should offer some comfort.

GPS is a point tracking service, resolving position to a specific given point, anywhere on the surface of the world, to a very high accuracy of generally less than 10m. This can be regarded as highly intrusive from a privacy perspective, as there is no escape. The system, if active, can identify exactly where you are, all of the time, to an incredible accuracy. This is highly effective for many applications, but is also highly intrusive from a privacy perspective, if users are tracked in this manner when they don’t need to be. In general, GPS is often regarded as a live system. Once a point is resolved, it can be immediately transmitted to a recording station.

Neomatrix is NOT a point tracking system. It is unable to directly identify points, but rather, it identifies routes. This is a very significant difference, and in particular addresses a number of privacy concerns in an elegant manner. Because it only works through comparing sensor data to known routes, there can be direct and simple transparency of which routes are ‘permitted’ to be identified. This is perfect for congestion pricing, where only main roads need to be included for tracking. This means that unlike GPS, the system can’t resolve users' positions anywhere other than when driving along main roads - which is what is needed for road pricing to be effective.

Video camera plate surveillance is an alternative to using toll transponders and toll booth gantries to detect vehicle toll tags. It is extremely expensive to install cameras, which means they can't cover all main roads effectively. It is also somewhat onerous for privacy concerns.

The recent London report on congestion as clearly stated that automated number plate recognition was dated, and that new technology to monitor vehicle use was needed.

For road pricing, vehicles must be monitored. Studies consistently advise that vehicles should be monitored per km and per time through main roads. Toll booths, automatic number plate recognition and congestion zones are regarded as 'Not fit for purpose' according to a recent and extensive government report on congestion in London. This report states that new monitoring technology for vehicles is needed to support road pricing effectively.

Retrofitting millions of existing vehicles is very expensive, and will have significant push back. Owners don't want government 'surveillance' hardware installed into their vehicles. Questions will be raised if this device records conversation for example. Issues of liability, who pays for the power, depreciating car value, damage, installer accreditation and so much more. In short it would be a PR nightmare to sell an installed tracking system to a city.

Road pricing should focus on small, cheap, removable devices that do not require installation or vehicle power. The public are happy to install a toll transponder on their windshield.

Neomatrix technology can be used in the same way, with smart toll transponders that detect position without toll booth gantries.

Neomatrix has developed a novel and useful method of highly compressing route information. This compresses a series of GPS points to a NeoTag, which is just a few characters. Compression rates of 99% are possible, yet the few characters in a NeoTag can be decompressed to reveal the exact route, including timestamps. Routes are not stored in a separate database, they are stored within the tag itself.

There are many reasons such compression is helpful, but the primary use case is for road pricing. Smart number plates or toll transponders may need to communicate a historical route taken, so use of congested roads at peak times can be sent to the toll authorities for billing.

In this context, there are very tiny batteries, as these devices can't be hard wired to vehicles for security, cost and other reasons.

NeoTags are so incredibly tiny, which is helpful for a small battery powered monitoring device to send just a few characters to communicate a lot of driving. Also, connection windows are also tiny, as vehicles speed under toll booth stations - and can't be paused to complete a longer transmission.

The NeoTag method is somewhat technical, but is perfectly designed for road pricing schemes which is what it was specifically developed for. The NeoTag method and use in smart number plates etc for road pricing schemes is subject to a pending patent application.

NeoTag is a compression format. Accuracy for positional information is retained 100%, however this is based on the snap-to-road positions, which is a very common processing technique. In almost all cases this provides higher accuracy than original source data for recording position, as it actually corrects most GPS errors. With this caveat, the NeoTag is lossless for compressing the corrected paths.

NeoTag accuracy for time information is lossy. This accuracy is configurable, with the highest being one minute accuracy, though the default is five minutes. So it can detect the time a vehicle was anywhere but not 'to the second' accuracy as may be driven or recorded by GPS originally.

Most use cases for recorded route information do not require such high resolution accuracy as per-second. To answer questions of what time was a delivery made, or what time did a worker leave a job, five minute accuracy is quite adequate, and noting this is a maximum error - the average will be much lower.

Additionally, human error in recording time manually (and slight errors in the time on watches etc) would be expected and accepted as within a few minutes. It is expensive in tag 'space' to record to per-second accuracy, and in most cases unnecessary.

For detecting speeding, the method records timestamps that can easily be used to identify significant speeding events, so long as they are not isolated like a relatively brief high speed overtaking maneuver. Any prolonged speeding would still be able to be determined from the compressed format, while privacy concerns can be reduced if isolated brief speeding isn't being captured or retained in the NeoTag format.

GPS works by trilateration of distance to three or more satellites, resulting in a 'triangle of error', where the position is determined to be in the centre of this triangle (10m error perhaps).

Neomatrix is not a point tracking system but a route tracking system. The error profile of the position is very different. In some cases the positional accuracy will be higher than GPS, and can be provided in areas GPS can't work - e.g. tunnels. But in other cases, it may be less clear. The area of error may be 500m or even more in extreme cases.

Provided the system is able to monitor movement in an ongoing manner as designed, it can provide reasonably high accuracy with confidence. Note that error reduces once the device moves onward, such that live error may be worse than historical error. Subsequent movement 'corrects' previously detected positions.

While technical aspects of road pricing are a significant barrier to adoption in monitoring positions, consumer acceptance is also a big a hurdle to address.

The privacy aspects are critical. GPS and any point tracking system is highly invasive for privacy. Consumers don't want to be tracked 24/7 or to high resolution. They don't want to be detected occasionally speeding, and they don't want their final destinations tracked.

Neomatrix addresses these concerns. By only being able to effectively track main road use, being unable to track final stop destinations accurately, and being unable to detect speeding unless sustained … Neomatrix gives privacy confidence.

Additionally, blockchain technology can be used to ensure in-car devices only transmit a verifiable toll bill for road use, without disclosing the tracked history, and this can also be done without linking to the driver or even the car, yet still provides a way to cryptographically authenticate the bill for use.

How a scheme is described is critical. Language is key. Sell benefits, not features.

Negative terms: Congestion tax, road tax, road pricing, road tolls..

Positive terms: Road pass. Peak hour passes. Fast Lane pass. Speed passes.

We are 'selling' the opportunity to travel at peak hour faster than now. Road pricing reduces congestion - so consumers are buying time, and thus traversing the network faster.

The word tax implies a sunk cost. We may not see benefits of this directly, and not as an individual. A road fast pass however, offers a direct and individual benefit to the driver. They are paying to get somewhere faster. They get something for their money. The fast pass should also be linked with direct and mostly larger savings in other existing road charges like annual tax.

Implementation would never be consumer cars to begin, as this is too large. Rather, heavy vehicles would be the obvious place to start. They generate the most emissions, cause a lot of road damage, and it's safer to have large trucks discouraged a little more from road congested times. These larger vehicles may already have or be required to use GPS tracking, so additional non-GPS tracking can be verified against actual fleet movement if there was need for additional testing of the system. Once the heavy truck fleet has shown to successfully operate under the faster and in some cases cheaper (if they modify driving patterns) road pricing system, it could be implemented for smaller trucks and eventually cars.

It's vital to make it very clear to all road users, that road pricing done correctly, can offer increased privacy over existing toll road system, cheaper road use charges overall, and of course faster roads and cleaner air. But consumer acceptance is of course a very big challenge, as many people will mistakenly see it as either privacy invading mass surveillance, or increase costs, when in fact there is the ability to introduce it with both these areas becoming 'better' than they are already today.

Traffic congestion is what occurs when too many cars try to use a road, such that they approach it’s maximum capacity. It results in far slower speeds, travel times, costs and pollution. The efficiency of the road network is also non-linear, such that roads can accommodate a lot of traffic, but above a certain point close to the maximum capacity, congestion occurs and slows everything down significantly. Strategies to keep roads at good capacity but with some room to move help to keep traffic flowing more efficiently.

City centres are becoming increasingly clogged with ride sharing vehicles, due to their low cost and convenience. People adopt ridesharing more now than public transport, due to their low cost convenience. Delivery vehicles are also increasing rapidly, as online shopping becomes the norm. A smaller factor is the natural increase in the city population over time.

While some may doubt, most agree we are on the cusp of realising self driving vehicles. Many expect these to begin being available within a year or two. Reports advise the floodgates will open as there is a massive shift to driverless fleets. Tesla for example has lease agreements that prohibit the lease owner from buying the car at the end of the lease. Tesla still sells cars, but is reserving the right to retain their entire lease fleet, as they have indicated driverless ride sharing is far more valuable than sales of cars outright.

The impact of driverless ride sharing vehicles has an ominous, looming impact for traffic congestion. With no driver’s wage to pay for, the cost of a driverless rideshare vehicle will be a fraction of current costs. Some estimates put the driver’s wage as 80% of the cost of the transport, meaning we could see ridesharing costs plummet to less than a third of current costs.

cnbc.com/2020/01/28/ubers-self-driving-cars-are-a-key-to-its-path-to-profitability.html

The seismic collapse of ridesharing costs will almost overnight result in a massive increase in demand for such services. There is a strong incentive for self driving vehicles to be on the road 24/7, as the cost to run these electric vehicles without a driver is just pennies to the owner. Sadly, the cost to the city is not pennies. In London, the current cost of traffic congestion is now £8 billion per annum (USD $10 Billion). With self driving ride sharing vehicles pouring into the network as fast as they can be built, this figure will sharply increase.

The USA’s Union of Concerned Scientists is a large professional body, dedicated to scientific research and reporting on big problems. ucsusa.org/sites/default/files/2020-02/Ride-Hailing%27s-Climate-Risks.pdf

This report states: A typical ride-hailing trip is about 69 percent more polluting than the trips it replaces, and can increase congestion during peak periods

Inventing a complete and viable alternative to GPS (for most terrestrial use cases) has profound global impact:

• Most smartphones will now use far less battery power, when using any location based services (mapping/tracking)

• Many IoT devices will be able to communicate full route history (all path movement), not just very limited GPS points

• Many IoT devices that have no GPS hardware installed, will now be able to both accurately track their movement, and also communicate this movement. The NeoMatrix NeoTag format can't be underestimated as highly novel and supporting ultra-low bandwidth sending of a path history. This can't be done with GPS, as it needs GPS points to first be compressed before sending, and this requires onerous power to perform the geo compression, unlike NeoMatrix.

• Many devices which were not previously location aware, could have very minor changes made, either as a firmware update, or a minor hardware update, to support monitoring of movement. A smart TV without a GPS chip might suddenly be able to reconfigure it's channel settings, language and support numbers for example, based on the new knowledge of it's regional location.

• In many cases, devices that logged some historical data (but not location data) could find the previous path history of these devices could be recreated from their history, if it can be processed by the NeoMatrix Position AI model. This could lead to some new forms of forensic analysis for law enforcement, or safety regulators.

• City planners now have a viable alternative for Dynamic Road Pricing, with monitoring mass vehicles, without the many issues with GPS such as power. Additionally, the NeoMatrix system offers unprecedented privacy controls over alternatives due to the fact it tracks movement paths, not locations, and can be configured to only support monitoring main road or hwy use, where GPS tracks position locations, and by nature of this technology can't be easily restricted to only tracking on toll roads as a 'toll both' would achieve for example. NeoMatrix is more akin to virtual toll booths on all major roads, for every km along these roads, but NOT supporting tracking on private or local roads, or end point positions in the same way as GPS.

• Legislation globally will need to change, to reflect this new form of surveillance. See separate section below.

• Smartphone vendors like Google, Apple etc will need to consider new user permissions for apps, as the existing permission for Location services no longer is suitable to cover this use case. NeoMatrix is already preparing proposals to present to these major vendors prior to full public use of the technology, to enable them to properly understand the new privacy implications, and what new permissions or changes are needed now, to protect user privacy. Given how the technology works, NeoMatrix believes existing permissions are simply not suitable for the new use case, and a new one is needed. The sensors used by NeoMatrix tech are not even specific as 'any input' that conforms to the required format needed can be interpreted by the AI, and sensors are routinely used for many purposes by app manufacturers, and there is currently no permissions on these. Adding new permissions on all possible sensors is unlikely to be effective, nor is rate limiting these sensors. The NeoMatrix AI can operate to resolve historical paths with extremely sparse polling, and sparsity only degrades path accuracy, not that the device took a given path at a given time. As they say on relationships, 'It's complicated!'

• The new ability to provide high quality and robust, offline GPS, means countries may reconsider their spend. The UK for example, allocated £92 million for just a feasibility study on it's own GPS system, after being cut out of the EU's Galileo system. www.gov.uk/government/news/space-sector-to-benefit-from-multi-million-pound-work-on-uk-alternative-to-galileo The core focus for the desire for the UK to have it's own system is reported to be civilian satellite navigation, and reports from the UK government estimated a £1 Billion cost daily, if the UK was to suffer other nations turning off or disrupting the free GPS signals it uses. www.thesun.co.uk/news/7122157/1billion-every-day-on-galileo. After spending eye watering sums, the UK discontinued this initiative, but the desire for sovereignty over satellite navigation is clearly a very big desire for national security. www.theneweuropean.co.uk/brexit-news/westminster-news/uk-goverment-could-rejoin-eu-s-galileo-system-92518

• The loss of satellite navigation (by denial, bugs, human error or natural events), even for a short term period would (now) be devastating. Food shortages, fishing stops, shipping slows, ports can't find containers easily... See this major report: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/619545/17.3254_Economic_impact_to_UK_of_a_disruption_to_GNSS_-_Showcase_Report.pdf and https://www.bbc.com/future/article/20201002-would-the-world-cope-without-gps-satellite-navigation reminds that one single person with a powerful GPS jammer could easily block GPS from all of London, or powerful solar flares could easily disable all GPS similar to The Carrington Event 1859 www.bbc.com/news/science-environment-46260959 which is why 'Space weather' is a major civil register risk.

Because NeoMatrix technology is so profoundly different as a global tracking system, this will require a vast number of surveillance and other legislation be updated to correctly cover this.

Some of the challenges include:

• NeoMatrix technology is not tracking positions. It can't track location positions like GPS, only historical paths. References to devices which track position or location may not now be covered, if there is no position or location tracked, but historical paths are tracked. It sounds a bit like an existential puzzle from Douglas Adams's famous book Hitchhiker's Guide to the Galaxy, or a Quantum Mechanics Schrödinger's cat puzzle. Was the device there? Where is the Device now? These questions can only be properly answered once the device is no longer IN the location. Only when it has LEFT the location can it be determined that it WAS there.

• NeoMatrix can't really track live like GPS. It can't with the core AI model, but can with a seperate post processing AI model. The nature of the tech is that there is only positional certainty well after the person or device has moved on some way, as the AI needs historical path data and returns historical paths. Historical locations can be very accurately tracked, but not current locations, and further, these locations are not directly tracked at all, but only inferred from the tracking of paths. There is a technical difference, and at no time is NeoMatrix method able to track positions like GPS as it doesn't work on trilateration like GPS, but by AI analysis of historical paths, based on multiple possible sensor inputs.

• NeoMatrix doesn't track any data about the person or devices position, or any data about them at all. Because we are tracking the natural environment, and not any external signal, we are not tracking personal information directly. The temperature of the day may not be regarded as personal information in the same way as GPS data for example, in privacy legislation.

• NeoMatrix AI technology involves a lot of prediction, and could readily be used for a device which only provides forward predicted locations of a person or object. Probable future locations are not really covered in privacy or surveillance legislation, and may require additional consideration by authorities.

• Legislation doesn't adequately define new tracking systems. This is because the NeoMatrix method is so novel, it was not considered before. Is tracking where we can't directly track positions? Is a device which can track paths but not positions still a tracking system? Is data surveillance a term that can be applied to the environment, which is not under any control or direct relationship to the person or device being tracked?

• All current surveillance and privacy legislation refers to geographical positions, yet this key term is not defined in legislation. This was never before a problem, as location is or was synonymous with GPS, and assumed to be within 10m error, or at least in that order of magnitude. Defining the limits of 'location' becomes far more necessary when tracking does not follow the usual error radius or even error profile and characteristics of existing systems that rely on one or more external reference points.

• Current legislation refers to a location, yet path tracking is not the same as point tracking, and the 'output' of this new method may be three or four positions, each could be some distance apart. The algorithms may apply quality of prediction to these points, but there can be no certainty in them in many use cases. If a device tracks and reports three or more points as the 'location', where one or even none of these may be 'correct', does this constitute a device that tracks location, when it doesn't return only 'one' location? At the extreme, a device that returns temperature could be regarded as a tracking device to establish if you are in the arctic circle area, or equator. Are these 'positions'? Clearly not, but legislation needs to draw some line in definitions, and hence multiple locations or probable locations, or future probable locations, or locations with confidence levels attached are all areas that now need to be considered in updating legislation, as a result of the new NeoMatrix Offline Positioning method.

• Is a low cost weather sensor, non-GPS mountaineer watch, or a tiny temperature iButton logger now classed as a 'tracking device'? A vast number of devices which were not previously regarded as a tracking device could suddenly become one, which could pose new problems quite apart from the legislative challenges of properly capturing the new method.

• Legislation refers to a tracking device as any device which can be used to determine the geographical location of a person or object. Recent technology allows image recognition to determine location for example. So a mere camera is now a tracking device, as any photo of a scene can often be used to reverse lookup the location from the image. Google Maps StreetView for example, is used to provide street view augmented walking navigation solely based on image recognition of the surrounding area.

Here are a few references to legislation, current as at 2021. Apart from surveillance acts, there is also additional legislation surrounding employment surveillance as well.

NSW, Australia

https://legislation.nsw.gov.au/view/whole/html/inforce/current/act-2007-064

tracking device means any electronic device capable of being used to determine or monitor the geographical location of a person or an object.

South Australia

https://www.legislation.sa.gov.au/LZ/C/A/SURVEILLANCE%20DEVICES%20ACT%202016/CURRENT/2016.2.AUTH.PDF Says tracking device means— (a) a device capable of being used to determine the geographical location of a person, vehicle or thing;

Victoria, Australia

https://www.legislation.vic.gov.au/in-force/acts/surveillance-devices-act-1999/040

tracking device means an electronic device the primary purpose of which is to determine the geographical location of a person or an object;

Queensland, Australia

https://www.qlrc.qld.gov.au/__data/assets/pdf_file/0007/591766/qlrc-wp-no-77.pdf

Tracking or location surveillance—the observation or recording of a target’s location. Location data may capture the location of a person or object at a point in time or monitor a person’s movements in real-time. It may also involve predictive tracking or retrospective tracking, based on the data trail of a person’s movements. Examples of location and tracking devices include global positioning system (‘GPS’) and satellite technology tracking, radio frequency identification (‘RFID’), and automatic number plate recognition (‘ANPR’).

Australia Federal Legislation

https://www.legislation.gov.au/Details/C2018C00464

tracking device means any electronic device capable of being used to determine or monitor the location of a person or an object or the status of an object.

Currently there are robust permissions handled by smartphone devices, to preserve user privacy. Users must explicitly allow an app to access the users location. This is currently done only by reference to external infrastructure, such as GPS, Wifi, Bluetooth or Cell towers.

However, location information CAN also be derived from non-GPS sensor data, which is not covered by existing location permissions. Hence there are standard rate limits or a special high sensor rate permission, or limits on sensor accuracy. This is because current technology needs high rates and accurate sensor data for say, inertial tracking. It doesn't work well for long, but does provide limited non-GPS tracking.

NeoMatrix Position Detection

So far so good. Except that NeoMatrix novel method can make use of sensor data in an entirely new way, that can determine users historical route information and position from either movement or environmental sensors, and can do so with very low sampling rates or accuracy. The AI is extremely good to take sparse, noisy sensor data, and return high quality location data.

While this novel technology offers incredible benefits to society, it also poses a significant challenge to preserve user privacy. NeoMatrix is keen to work with providers to establish new privacy permissions and a framework that can support the legitimate use of this technology.

Existing permissions are not fit for this new purpose method. NeoMatrix doesn't require access to any existing location based sensor, and as such can track locations using smartphones that have the existing Location permission switched off, which is a privacy concern. Existing sensor or accuracy rate limits are also not adequate to preserve privacy from this novel approach to location sensing.

Add Sensor Permissions

You may think the simple solution is to add user permissions to sensor data. All sensor data. However, this would cause more problems. First, almost a large number of apps make use of sensor data to detect e.g. screen orientation or activity. Adding new permissions to thousands of apps would be onerous for users, yet would actually be bad for security and privacy. Users would be 'trained' to expect that many new apps require sensor permissions, so will be used to clicking allow frequently. This is a problem as unwitting users will not be able to know when to not allow access to sensor data, and if they did deny access to sensor data, a lot of existing apps would not be able to function properly.

Yet the 'do nothing' approach means overnight, any app using sensor data can now potentially track a users route in high resolution, from sparse, noisy sensor data, and without the barrier of any permissions or restrictions in the operating system. Core sensor data is currently seen as low grade, and does not have any permissions.

As such, it appears a challenging privacy problem.

Proposed Solution

NeoMatrix seeks to work with providers and governments to establish new framework and permissions to ensure responsible and secure privacy permissions are established.

Proposal 1 - New user location permission

A new location permission be established in Android, iOS and other operating systems, asking users to 'Allow app to access sensor based locations'.

Note: The new method is completely different to all existing location services which are point based. NeoMatrix technology is not point based locations, as points are extrapolated from paths, not the usual paths extrapolated from points.

In a way, this permission is more about the sensor data itself than the locations. It effectively means 'Do not add noise masks to sensor data, to disable location sensing' (See proposal 3).

An alternative permission name could be 'Allow high accuracy sensor data (can also be used to determine location)' This seems more relevant if the app use case was not specifically seeking to determine location, but either way the user should be aware they are granting a permission that can be potentially used to track them.

Existing location permission not suitable

We accept that the new method is quite technical, and will not be easily explained to users no matter how you word it. The current standard location permission is not adequate as is to cover the new technology, because it would need to unnecessarily block sensor access, or degrade it either significantly or with noise masks. So if the user has allowed location permission, then the new sensor location method can be used without further prompt to the user.

The proposed new permission is solely for apps that use the new method, where users or the app itself may not allow access to standard location methods, and so not require their permission directly.

An app that has no interest in tracking the users location, but does require high accuracy sensor data may then need to prompt for permission to access sensor locations, solely to ensure their sensor data use has no noise or onerous rate or accuracy limiting applied. Apps that use sensor data but don't care if subtle crafted noise has been added needs no such permission.

Proposal 2 - Add method to location API's

We seek to have the sensor location method added as a new standard location data source, for use in location based sensor fusion API's.

This is not quite to enhance or preserve privacy directly, but ensures users are adequately informed about the possible 'source' of their location data. Users who allow location access do not currently need to be specific about source, but approximate location data should not be permitted to use this source, as it would be regarded as a precise source. Alternatively, the source could be used but accuracy degraded with added noise to ensure it is not precise unless permitted.

Adding this source to existing fusion API's will also greatly reduce power consumption of all location based applications, and enhance accuracy.

Proposal 3 - Sensor location noise masks

Current privacy proposals relating to rate limiting and sensor accuracy are not suitable to defend against the new sensor based location technology. However, highly complex solutions are possible, to allow apps to use sensor data as usual, but to deny 'location sensing'. This is a non-trivial approach of adding noise to sensor data that is specifically crafted to mask location information.

Currently, map providers and other data vendors add 'noise' to watermark their data and prevent copying (e.g. a false road or curve angles etc). NeoMatrix proposes the reverse in a way. Requiring the addition of noise by operating systems, to sensor data API's to 'remove' location data which is otherwise identifiable just like a watermark is identifiable to the vendor for their IP protection.

For users which have not allowed the new permission to 'Allow app to access sensor based locations', the special noise mask is applied. If this permission is allowed however, then the sensor noise mask is not applied.

Under general use, users of apps requiring sensor data should not notice any added noise, but while very subtle, this added noise will degrade the sensor data enough to deny location sensing, without disrupting current widespread use of sensor data by large numbers of apps.

Proposal 4 - Updated privacy and surveillance legislation

The new method poses significant challenges to existing legislation globally. More on this topic is found in NeoMatrix FAQ.

Sensor permission resources

Below are several links to relevant topics covering issues around access to sensor data, and location permission privacy.

https://www.w3.org/TR/generic-sensor/#location-tracking

https://developer.android.com/guide/topics/sensors/sensors_overview#sensors-rate-limiting

https://developer.apple.com/documentation/corelocation/requesting_authorization_for_location_services

https://developer.apple.com/documentation/coremotion

User location data is about as intimate as it gets in privacy, along with address, DOB and contact details. Some may argue it's the pinnacle of privacy concerns, and evokes Orwellian, dystopian panopticon like themes. Being watched everywhere you go at all times, sounds, well, somewhat unpleasant to say the least. Yet GPS has been available for around 40 years now, so what's different with the NeoMatrix technology in terms of privacy in tracking?

GPS has so many technical limitations, that long term, lifetime precision tracking has not ever been reasonably possible with current battery technology and so on. More recently, Tile and Apple AirTag came along. These solve many issues with GPS, including supporting long term tracking. However, they do not support high resolution route tracking. They are static location trackers, not path trackers. Still potentially very privacy invasive, but somewhat limited in their ability to provide full route information, or historical address information. However, the Airtag especially opened a huge debate on privacy, due to how easily that can be used to stalk other people (for bad reasons, not say, valid investigations), or to assist in crime - such as tracking fancy cars to find out where best to steal them from.

To Apple's credit, they had some protections built in to their AirTags, to notify users if they were being tracked by an AirTag after some time. Getting the balance right between a tracker used to prevent crime vs enabling it is extremely hard, and its impossible to please everyone. You don't want your bicycle stolen, only to have Apple helpfully notify the thief they are being tracked, and encouraging them to find (and destroy) the tracking device.

This space has ongoing debate. NeoMatrix has a proposed solution to address and improve user privacy in tracking services.

User location privacy is critical to preserve, but recent advances are causing a privacy perfect storm. We have rapid advances in technology, in IoT, in network infrastructure (Airtag / FindMyDevice, Amazon Sidewalk etc), rapidly improving battery density (to improve device operation life), rapidly shrinking electronics, increasing sensor type and resolution quality. We also have amazing advances in AI to make sense of all this big data in ways never before imagined.

The proposed solution is to take the Apple initiative of user notification, and extend it to all major players in the space. A single source database should be provided of tracking, so any device can check if it's being tracked, without legal covert authority. Obviously protections must exist for law enforcement to hide tracking of criminals or in investigations, but for private individuals, we should not need an Apple device to be notified, OR download an app from the Android store to 'check' if being stalked.

All tracking platforms above a certain minimum size (to not discourage startup tech etc) could be legally required in their countries, to provide tracking signals to a central database. If this was the actual tracked paths, this would be problematic and a privacy nightmare. However, like face or fingerprint recognition, we don't NEED the tracking path data, we only need the signature. A privacy friendly database could be constructed easily, that contains no information about user movement, but does allow notifications of tracking without consent.

Any user with any device could 'consent' to their location fingerprint signature being provided to the service. If so, the service will notify them if they are being tracked, for more than a given period. We need to allow short term tracking to facilitate theft prevention, but prevent longer term 'stalking' type tracking.

The service collates signatures from all major vendors of tracking services, and where there is a match, where two or more signatures match, the service notifies the vendor. Neither the service or vendor will know where the user was going, or who was tracking, only that tracking did occur, and over what period. This supports user privacy, while also supporting user discovery of unauthorised tracking for stalking or crime purposes. A central body means the service is device agnostic, and statistics of such breaches can be provided to researchers, to better understand the domain.

Users can select permission:
[ ] Detect unauthorised tracking (Upload my anonymised location data)

Another feature could be considered, being a prevent notification warrant. A car stolen with a tracker could have the user notify police, who if they apply in time, could seek to prevent the theft causing the thief to be notified they are being tracked. This allows law enforcement to be involved, such that you can't track for bad reasons as user notification will occur, yet if you have got some item stolen, then, with Police authority, you can prevent the thief being notified. It would then likely mean the user ceases to be notified of movement, but police are then able to take over the monitoring role, without such notification.

The key aspect in this proposal, is an industry body being set up to work with all tracking technology providers, and mandating all such tracking data be centralised, but also anonymised. This addresses a lot of privacy concerns of the new tracking tech that is emerging, being incredibly tiny devices that can track anything anywhere for years. We need better privacy protections, and a concerted, industry wide solution to work with law enforcement and all major vendors is an obvious solution. Apple was criticized when AirTag came out, because Android users could not access the user discovery of being tracked. While this has now been addressed, it highlights the concern in tracking technology more generally. As more services become available, how do users discover they are being tracked, in ways that are not lawful, and they do not consent.

The NeoMatrix team has a number of technical solutions to this user privacy problem, using encryption and signatures, and would be keen to work with any industry player or government who seeks to improve user privacy in terms of rapidly developing new forms of tracking technology.

Interest is growing in the space of companies seeking alternatives to GPS for navigation.

NeoMatrix now has a good working solution. Here are some other technologies and initiatives.

https://spectrum.ieee.org/an-alternative-to-gps

https://spectrum.ieee.org/us-transportation-officials-seek-alternative-tech-for-gps

Our Gilbert app is smart, and can determine your historical paths travelled, without using any GPS at all. But as with any new technology, there are some caveats and understanding. In perfect conditions, Gilbert can rival GPS for accuracy, but it can also get confused. R&D is ongoing to continue improving accuracy, but for normal expected logging, allowing GPS access is helpful. NeoMatrix technology requires special maps to be prepared for our AI to be able to interpret your sensor data. It won't work at all if we have not 'imaged' the area you are in, or if your movement is wildly outside expected parameters. If you catch a plane, or drive in circles a lot, or otherwise move in less expected ways, Gilbert may get confused.

The app may take longer to reacquire your location, and require a period of 'normal' movement to do so. GPS is also helpful for analysing our technology as all routes captured are collectively anonymised and used to further improve the maps, exactly as many other major location technology companies do.

If you allow the GPS permission in the Gilbert app, it just means your current location is more likely to be live, likely to be even more accurate, and Gilbert can let you know if you are located within a city we have not imaged yet for our position sense technology. So Gilbert absolutely does not need GPS, Wifi, GSM, BlueTooth, NFC, Microphone or camera. We don't even need an Android OS permission to sense location! So we have built our own permission, and are actively seeking the issue of position sensing be covered more officially in user permissions, to preserve privacy. Amazing technology can sometimes be ahead of the curve a bit, and regulations take time to catch up. We are doing our bit to ensure no surprises here.