BrokeInBendigo

QGIS with govt-provided datasets and georeferenced old maps. A bit technical to set up but hard to beat. Tumonz also great, though I've not seen the latest versions.

That intro video is hilarious. Like comically overblown hype with similarly comically bad CGI. Lol!

Guess the coin and relic crowd is a bit different than the gold crowd. 

1 minute ago, GotAU? said:

If it were a pure gold nugget Inwould expect it not to contribute to the halo, however the precipitates of iron, copper and other metals that were present with the gold in a buried nugget could leach out into the surrounding soil and create a larger halo target around the nugget.

Maybe a tiny amount of material would leach out but only the outermost molecules in the nugget would be exposed to the environment.

I'm more referring to the depositional environment - the bedrock or clay or whatever acts just like a sluice to catch gold particles. It also catches heavy materials like iron-rich minerals. Those other materials are concentrated along with the gold contribute to the response. When you dig, you disperse all the other stuff and the response is no longer the both gold + nearby concentrated minerals, it's mostly just the gold, hence a lesser response.

Nugget halo makes sense to me. You'd expect iron-containing heavy minerals (ground noise) to settle in along with nuggets. It's not that the gold itself is interacting with its environment, but that the process that guides nuggets to their resting place also accumulates materials that give a bit of a signal. 

When digging, you break up the previously concentrated and defined volumes of metalliferous material which surrounded the gold. 

I'd be confused if a nugget in its "original" spot *didn't* sound different than the same nugget buried at the same depth, with same orientation, in the same now-disturbed ground.

Talk about Real Hard Yakka™️ country! I suppose prospecting style picks will do pretty well on ice.

On 8/14/2022 at 3:43 AM, cudamark said:

Yes, confusion abounds when you start talking American to an Aussie or Kiwi. Order biscuits and gravy in a restaurant and see what looks you get! Getting pissed has a whole different meeting, not to mention the word fanny! 😆

A major lesson learned after moving to Australia is that friends here use words that, in the states, you don’t even use for enemies (much less suitable for this forum). JP’s post was actually quite warm and fluffy relative to the usual vernacular. 

Gerry,

Might wanna slow down there buddy. There are some older folks on this board that need to watch their blood pressure. 

Great results Simon. I expect ML will replace the 11" coil. Hopefully they take responsibility on a larger scale for the apparently quality issues with the coil and detector.

10 hours ago, Jonathan Porter said:

A lot of the X coils will not Ferrite balance properly especially in Normal timings, the best ones I used were the 15” Concentric’s they weren’t too bad, although a friend of mine has told me his recent 17”CC coil is very good too. The reefy country will most likely be saturation signal being magnified up the centre of the Ferrite, use the in-air approach assuming the coil and timings you select will allow it.

The GPZ14 coil should be able to ferrite balance in all timings (it is OK to have some small amount of signal but a loud target-like one is not good).

If you can achieve a reasonable X balance then I highly recommend you use the Semi-Auto GB mode, once locked the X calibration cannot shift unless the temperature of the electronics shift a lot (can only shift a few % points from dead cold), however if using Auto in some ground types you will only need to walk 20 meters in Auto and the conductive and saturation signals can throw the Calibration right out, this then has a flow on effect with the G balance which then tries its hardest to compensate but WILL fail.

In the conductive areas in the US (Nevada etc) the X signal is probably minimal and the Alkali the worst so the Auto mode should not be too badly affected by a bad X balance, best way to check is to pass the coil over a ferrite occasionally and see how loud the signal is, personally even though there is not much X present I would still be using Semi-Auto if for no other reason than it might give me a slight advantage over other operators.

My experiences in Arizona showed me there was plenty of X signal to be had in and around the Bradshaw mountains, even up at Rich hill there was plenty of ground that was variable (this was in the days before Smooth, GP3000 from memory) and I’m sure there would be plenty of X signal around. Mineralisation that forms gold that is then weathered has all the elements that can affect a metal detector no matter where in the world we work, if it didn’t then Americans would still be using VLF machines there would be no point to a PI. Case in point the new Garrett Axiom, obviously there is still a need for a PI in the US.

JP

 

 

Thanks for your detailed posts JP. 

1 hour ago, Jonathan Porter said:

What coil do you have on your machine?

In some ground where there is a bit of saturation signal the round ferrite will channel that signal up itself magnifying it, this can sound like the Ferrite isn’t being balanced out but in fact it’s saturation signal, you cannot ground balance out saturation.

Best bet is to place the ferrite on top of a big rock (4 inches or so high) or put your ferrite on a stick and hold the coil away from the ground waving the ferrite under the coil over the windings till the noise goes (with QT depressed of course), then bring the coil to the ground and slowly pump the coil till the Semi-Auto GB balances out the ground signal. (The GB for the ground will be out because when the coil is held in air you are balancing to nothing as you calibrate to the ferrite).

If there is only a small signal off the ferrite don’t worry about it, the key is to not have a LOUD target like signal on the Ferrite. General ground noise will cover any mild signals especially when using Normal.

The Most sensitive mode on the 7000 to the ferrite is High Yield Normal.

 

 

Thanks JP.
 

I have a stock 14” and month-old 17” CC x-coil, believe it is bundle wound (edit: tis spiral, thanks Simon). 

Out bush in reefy country with a lot of ironstone or red mudstone type bedrock I often get a fairly loud signal on the ferrite but on alluvial gravels or paddocks it’s less intense.

I’ve been running auto but understand the advantage of semi auto - I’ll try that and your suggestion about elevating the ferrite today. 

I can "balance" the ferrite out in Difficult using the QT button but cannot balance it out in Normal. I've done the octopus (as described by @Jonathan Porter ) manoeuvre for 1 to 2 minutes over the ferrite, still hear it. Especially if the ground is hot. Am I doing it wrong?

3 minutes ago, Valens Legacy said:

...

I have no idea  if AI could ever work on a detector for any useful edge in this hobby. Computers are only as good as the programmer and today detectors are more computers on a stick.

...

This is the big shift with machine learning (what we are, for convenience, referring to as "AI").

Computers are no longer only as good as the programmer. Computers are better than the programmer - much, much better.

Perhaps disturbingly, the programmer has no functional access to the logical process an AI uses to make a given decision. It is too complex and abstract, humans generally cannot understand it, despite being able to analyse that decision-making process.

Put a coil on an AI and you could have a detector that rivals and even surpasses the work of human genius.

Just one example of machine learning revolutionising a data analysis problem (which humans have spent a very significant amount of time and money on): https://www.escardio.org/The-ESC/Press-Office/Press-releases/machine-learning-overtakes-humans-in-predicting-death-or-heart-attack

10 hours ago, Ben201000 said:

Thanks for the paper! 

Thank you all of that post. There was so much in it. I'm new to everything to do with detecting so all of it was extremely helpful. What are your ideas on other methods of acquiring the signal? Is multi frequency analysis something that could be used?

I was thinking an approach to this could be to use a similar approach to photogrammetry or biometrics. Only using image and no location data. The phone/drone/AR glasses would map key points of each image and an AI detects the location of the coil against the image.

I'm doubtful if this could work right now, but I 100% think it will sometime in the future. 

In regards to you mentioning that induction is maxed out, are there any new alternatives? Maybe technologies that pick up so much that they're practically impossible to turn into a human interpretable audio signal, but could all be feed into some kind of neural network? Is multifrequency something in this direction? 

Here's a moderately technical paper from Minelab (who, at this time, makes the best pulse induction prospecting detectors): https://www.minelab.com/__files/f/11043/KBA_METAL_DETECTOR_BASICS_&_THEORY.pdf

More basics (see Multi Period Fast, Multi Period Sensing, Smart Electronic Timing Alignment, Zero Voltage Transmission): https://www.minelab.com/anzea/knowledge-base/key-technologies

Some good info in there. Minelab does use multi-frequency TX and RX but their analysis is magic sauce. Imagine they have some sophisticated analysis. As you well know, if there was AI involved anywhere, their marketing would ensure we know allll about it.

Alternative avenues of improvement include ZVT (as mentioned above, this was the main innovation in the GPZ 7000, released 2015, new updated model on same platform expected in the relatively near future) and innovative coil design (for example, the recent rise of concentric coils for the GPZ, some recent patents for coils in which a flat-wound coil is twisted at front and rear to be vertically oriented, to reduce saturation from ground mineralisation and other designs).

1 hour ago, phrunt said:

Yea, I don't think I've ever used tracking on the 4500, but in saying that I'm the person least likely to need to use it, I was always on fixed and manual is my go-to on the 7000.  The more detector manufacturers can improve ground balance the better depth the users will get, I think people in hotter soils would get a surprise the depth difference between having any ground balance and ground balance disabled.  For example, the GPX 5000 with GB completely turned off, not fixed, off completely gives so much more depth than the same detector with Ground balance enabled and balanced in mild soils where the detector gets no reaction from the soil with it either on or off.    The QED was the same, in any mode other than Mode 11 (GB Disabled) in mild soils even with a perfectly balanced detector the depth is killed just by enabling the ground balance circuit.  I guess in a way Geosense is working towards this, I would still like a way to disable it on the 6000 just to see how it works for me.

In some of my prospecting areas I can run both the QED and GPX 4500/5000 with ground balance completely disabled and they remained perfectly balanced, no reaction from the ground at all, the down side is by disabling it the hot rocks really come alive so the area has to be selected carefully to take advantage of it.

The better manufacturers can improve the detectors ground balance the better the depth will be and if they can use some sort of AI technology to do this or just faster processing or whatever it will be the next big improvement in PI's.  I always thought that if I used ground balance and balanced the detector I'd get the same depth as if I had ground balance turned off entirely in very mild soil, and this is simply not correct.    My mild soils are the perfect example of this as even though I can run with no ground balance at all, just by enabling it I am hindering depth.

Exactly. Your experiencing running with GB off illustrates how much detecting depth depends on the ground handling. 
 

Think I’d still rather have our Aussie sized nuggets and hotter ground than your mild soils and fine gold 😅 hope you can make it over here some time for a prospecting adventure and smash some personal bests!

2 hours ago, Norvic said:

Aye, very rarely used a GPX in ground tracking (other than the 6K) same with the GPZ 7000. Manuals been the go, auto tracking probably is part of the evolution of our detectors to AI, Geosense probably another part, hope I`m around to see AI compete with what we have between the ears.

Simon’s referring to no ground balance at all - not fixed/manual GB - which is a setting I’d wager nobody uses on Australian goldfields. 

1 hour ago, phrunt said:

While I've never owned any model of GPX below the 4500 both my 4500 and 5000 can turn the Ground Balance off.

...

Thanks, had no idea this was an option! 

45 minutes ago, Chase Goldman said:

Immense?  Um, ok. 

Not sure what you mean by silent threshold, but OK.

Induction-based detecting tech has plateaued.  But I can't fault folks for wanting to squeeze more blood out of a rock.  More power to you and your unbridled optimism and enthusiasm.  Would be more than happy to be proven wrong.

Meanwhile I'll focus most of my energy into site identification and using tech and research to find sites likely to produce and methods to thoroughly exploit them for coverage.  Much greater return on investment than micro incremental improvements in an applied principle that has been fundamentally unchanged for 100 plus years despite the latest advancements that have delivered incremental improvements through SMF and signal processing.

Meant stable threshold not silent. 

Almost all of the tech in a PI detector is there to separate of signal from noise. When you run your detector at anything besides the highest sensitivity settings (so on a GPZ, that'd be Sens 20, all smoothing off, Normal - on a GPX 5000, that'd be Sharp timing, gain 20, stab 0), you are sacrificing depth for stability. Every setting under those max settings is there to help filter out ground and EMI so you can actually distinguish real targets. Even those max settings have some amount of ground and EMI mitigation built in. 

If you can run balls to the wall settings where you are and still not ever be affected by ground noise or EMI, have zero false targets, well I would love to be there! But I suspect that you do not run your GPZ or GPX full-bore all the time, and therefore you are missing targets. I think there is a lot of blood still to squeeze out. 

The QED is one detector that has a no GB mode - not aware of any others - and it is unusable in that mode in even marginally mineralised ground.

Of course, the detector manufacturers and engineers are the ones who will improve the tech. The prospectors are doing what you want to be doing - prospecting.

Machine learning can do things today that only the most visionary humans dreamt of in the past. There's massive potential for a new era that dwarfs previous technological generations in terms of scope and capability. It's hard to overstate the potential, but very easy to dismiss it as incremental. It can and should be applied to detector technology and will likely have a massive impact.

11 hours ago, Ben201000 said:

Hi BrokeInBendigo,

Thank you for both such in depth posts. I'll do my best to try and summarize what I understand from them and then add/ask anything more. 

First it isn't very useful (potentially impossible) to detect between metals. It is far more useful to balance the ground and reduce EMI. Is this because EMI produces a lot of noise and leads to digging holes without any metal in? Or is it mostly distracting and mentally tiring over the hours? 

Secondly the ground conditions can vary enormously, essentially making a single model that knows everything impossible. Do the ground conditions vary hugely within one detecting session or is it more in different geographical areas? 

Something I hadn't considered was the scale of the area. I.e would a very experienced detector walk through a 5 kilometre square area and be able to narrow down a few 100 meter square areas that are worth detecting? If so, could AI be useful attached to a drone that scans a 2km area with various sensors attached, and then tries to narrow a few 100m areas to look in. As I write this I realise getting training data for this would be extremely hard. 

I really like the ideas around having a screen showing the raw waveforms. 

It seems from everyone's response that conditions can be so variable that the AI would have to be trained on each separate detection session. This presents a few challenges but could be possible. YouTube/Spotify etc all train customised AI models for each person. Right now it's possible to take about 30 photos of a bird vs not-bird on a hike, and train an AI in about two minutes on a standard laptop, with about 90% accuracy (not a hugely relevant example, but this was unthinkable 7 years ago). Of course no one wants to carry a laptop around, but there are AI specific training chips which are tiny. One on the iPhone as mentioned, but also more specialised ones like the Google Coral and Nvidia Jetson Nano. There is also the possibility of sending the waveforms over to servers to quickly train, but I imagine there isn't any 4G where everyone is detecting. 

Latest thought: There is a small AI training chip (no larger than a smartphone), with a screen (probably use smartphone app for it). The raw waves from the coil somehow connect into the chip. There are 3 buttons on the screen (label 1, label 2, train AI). When someone reaches the specific site they begin by choosing the labels. Maybe metal vs not-metal, but it could be anything depending what the detector thinks could work. As you dig holes you click which label it turned out to be. After say 30 holes you click 'train' and wait about 2 minutes. It then starts giving you a real-time prediction in a percentage of which label it thinks the coil is detecting. 
In no way does this replace the detector, you'd still use your usual method, there would just be something extra to test against. The approach of this method would be to have little AIs that are personalised to each persons local knowledge, and these AIs are each persons property unless they decide to share them. They may find that it works well distinguishing between two local features and they use it for that. Or that training after 10 samples is handy but they only trust the results about 40% of the time. Or that 500 samples is required, but that's okay because they regularly detect on similar ground. Or they upload and combine data with others in similar ground conditions. 

My last thought was that to collect data wouldn't it be possible to bury a few known items and scan over them in the specific soil? Or on a larger scale bury lots of samples in an area and scan over at different heights, add more soil above and scan again etc? 

To clarify how 30 samples could possibly work. We could use transfer learning on an AI trained on millions of images (called ImageNet), and then it is taught the new samples. Some people have had a lot of success turning waveforms into images and then training them with this AI. 

Thank you so much for the Dall E prompt booklet! I've got access to it so will definitely have a read through. 

Also are you in Bendigo, Victoria, Australia? I'm in Melbourne 🙂 

You're most welcome. I've a keen interest in this, so please excuse if I go on a bit long about this stuff.

Balancing and EMI

It's most important to balance the ground mineralisation because a target on the edge of detection cannot be differentiated by the detector operator from the response from the ground.

To elaborate, I'll just describe a bit of how pulse induction detectors work. The coil is energised with varied intensity and at varied intervals. The pattern constitutes the "timing" involved. The detector transmits a pulse or pattern of pulses and then is set to a receive mode to get a response. TX/RX cycles are very fast.

The timing you select is largely dependent on the ground type. Some timings are higher-energy than others. The more energy you put into the coil, the better the response on gold/metal, so you want the highest-energy timing that will work in the area.  

Problem is, different ground responds to different timings in different ways. For example, the ground may be saturated to a significant degree with iron-rich minerals (generally in an area where quartz reefs occur) or salt (dry salt lakes), or have far less mineralisation (granitic sands). Some ground types will produce responses very similar to a piece of gold with a certain timing. The higher-energy timings may be unusable in these areas because the ground looks more or less the same as a metal object at depth. In other words, it sounds like there are targets everywhere (on current detectors). 

You then switch to a lower-energy timing, or perhaps a timing with a different pattern of pulses, which does not produce as much of a response for that particular ground type. In doing so, you lose detection depth. 

Regarding EMI, it is a similar situation. When near sources of EMI (e.g. power lines) at frequencies and amplitudes such that they energise the coil, again you get a response that is very similar to a real target. 

In both cases, there are a variety of settings on the detector, some of which process the data stream before it is converted into audio and some afterwards. You could use a higher-energy timing but reduce the gain at a particular point a the processing chain, or apply whatever kind of DSP method. A common one is "stabilisation", where you ignore low-amplitude variations in the signal. Reducing the amount of data being converted to audio reduces audible responses of course. Sometimes it's better to have a quiet detector with less sensitivity, other times a noisier detector with more sensitivity. The operator and their experience is a major factor in setting choice.

So what we need to improve in current detectors is the handling of the ground response, when using the highest-energy timings. We need to separate the signal from noise, which I believe is a task very well-suited to an AI.

Ground Conditions

Ground conditions can be and very often is variable in very small areas. For example, you may have an iron rich area of bedrock that is visible at the surface and then slopes downward, at which point it is covered in a mostly organic soil. Swinging the detector across this boundary of soil to ironstone will induce a response. Another example is a quantity of soil which has higher capacity to retain water than an adjacent area (again, this could be within a square metre) - this will cause a response. Of course, across larger regions you have trends as well. 

The timing used can reduce/eliminate the response at these boundaries, at the cost of detection depth.

Training/implementation

Your idea is fine, but I'll reiterate that you absolutely need an existing algorithm processing the ground for this to work. Nobody wants to dig X holes just to get started in a particular spot, it's not feasible. You'll understand when you recover 30 targets 🙂

Burying targets

Not gonna work. Metal objects in the ground have been there from a few decades to literally millions of years. The presence of the objects in addition to all that time create profoundly different conditions than what you'd get if you buried something. A common technique to somewhat obviate this is to drill holes from below the desired target depth and insert a test target. This allows the ground above the target to be undisturbed and provides a more realistic testing scenario. 

Still, it won't really work because of the extremely diverse range of ground conditions in which gold is found. The only real use of testing on buried targets is comparing different detectors relative detection depths, and even then it's a very smooshy, vague kind of testing. 

Waveforms to Images

Sounds like a reasonable method. I had a lot of fun coding an app to interpret an image as raw audio, then apply audio effects to it, and finally re-interpret it back to an image. I mean, a waveform is just a 1 by X image, right? 

Yes - In Bendigo at the moment. I think the majority of this site is focused on the US but plenty of Australian fossickers and prospectors here.

11 hours ago, Chase Goldman said:

No, that is really easily sorted and works well right now.  Tracking algorithms work well, also.  I am sure AI could be applied but really you have a solution looking for a problem when it comes to ground tracking, to be frank.

...

Hard disagree. The increase in targets recovered if we could use the highest-energy timings in all areas, with perfect ground and EMI handling (meaning silent threshold), would be IMMENSE. 

11 hours ago, Ben201000 said:

Hi Redz,

Excuse me for the extremely dumb questions, but are hot rocks rocks that read similar to metal? Are there certain areas where there are lots which makes it harder to look for metals? 

Hot rocks are metal-rich rocks (sometimes also mineralised with gold!) which sound like a nugget. Some areas are covered in hot rocks and your options are to either tune down your detector to ignore them (and necessarily miss some gold) or dig them all (and spend a lot more time digging).

7 hours ago, jasong said:

Inertial navigation using accelerometers and then dead reckoning is far more accurate than GPS for moving systems. It's sufficient for things like general ground sensing. When used in combination with mag sensors and coil data, you could achieve sub-inch resolution easily. 

Essentially you would make the ground it's own reference frame while swinging the coil using inertial navigation, and then tie that high resolution work "chunk" to a traditional lat/lon reference frame via GPS. 

I've suggested this a few times, and there are other applications - an accelerometer could be used to know the detector is in a "target recovery" mode and it should not do any ground tracking. It could also be used with an AI to recognise small-scale geological boundaries and not give one-way responses when crossing them. Would I want this? No, I'd rather hear the ground changes. But still interesting.

6 hours ago, Dutchman4 said:

...

Do you really want an AI based, all knowing, detector to reduce you down to the mere unintelligent functions of swinging and digging? 

I absolutely want my detector to handle as much extraneous information processing as possible. I want to use my prospecting knowledge to determine where to swing and turn my detector sensitivity as high as it can go.

5 hours ago, Sourdough Scott said:

I'd be curious to see how AI could be applied to geology and mapping of ancient gold bearing rivers? From what we have now to what geologists have previously discovered and published their findings. Possibly could be a useful tool in future gold patch hunting. 

You may be interested in looking up geophysical interpretations. I don't know if AI is being used in this area but such datasets are extremely interesting.

Recent Apple iPhones have a dedicated processor for machine learning tasks. You don't need crazy hardware. Well, modern smartphones are kinda crazy with how much power they have, but still, it's nothing exotic.

Another idea is to simply update the ground and EMI handling on a regular basis via software updates.

While the detector is in testing/development, a lot of training data is acquired. The detector/app doesn't need to be sophisticated at this point, the app would just record all raw data from the coil and your beta testers press a button on the app when they believe they have a target, then press another button after it has been investigated to confirm if it was metal (and what exactly it was perhaps), or if it was just ground noise/EMI.

You'd also have some people going out in various goldfields to very carefully and methodically generate high quality training data.

After your testers gather ground responses from all over the world and have timestamps for targets, you give this to a NN to figure out a model. You'll need some slack in the model of course, as humans aren't perfect.

Afterwards, you have a pretty good model. This is implemented to the detector on release. People who agree to continue helping to develop the model continue to mark targets as real when found as described. This data is given back to the developer who continues training the NN with this updated data. 

Unless a large number of people poison the well, your model will only improve as time goes on. You'd have two release channels for the model, stable and testing, which you could select in the app. Testing would be the latest changes, which may or may not be better than the stable model.

Major takeaway: You don't need to engineer or even understand your signal processing pipeline if you let a NN do it. In other words, you don't need to really understand how a metal detector works to make a very, very effective machine.

Edit: You could have different NN for different regions. For example, you could have a Pilbara model, a Ballarat model, a Clermont model, a Nevada model, etc... You could give GPS coordinates to the algorithm and have extremely specified ground balancing... The possibilities are mind-boggling. If you want to see how paradigm shifting AI can be, have a look at DALL-E 2, an imagine generation model. Here's a mind-blower of a PDF giving a lot of examples: http://dallery.gallery/wp-content/uploads/2022/07/The-DALL·E-2-prompt-book-v1.02.pdf

Hi Ben,

I've thought about this quite a bit. I think would be trivial for a neural network to sort it out. There are only a few primary dimensions to the data - it's just electrical current from the coil, that is the only sensor detectors use.

However, I think you are slightly misguided in where to apply the AI. Metal target differentiation may yield some interesting results but you can make NO assumptions about the mass, volume, shape, texture, and mineral inclusions in samples of native gold. Gold often contains silver, copper, and iron, among other metals. I have a gold nugget that is over 1% palladium (not platinum!). Gold is present as jaggedy, branching crystals as well as smooth and solid nuggets. It is found distributed through quartz and ironstone. I am deeply sceptical that any algorithm could accurately differentiate gold from not-gold.

Where a neural network would do wonders is with ground balancing and EMI cancellation - that is, the capacity of the detector to ignore everything except a solid metal object. This is what holds detector technology back far more than lack of target identification.

Such a NN-developed algorithm couldn't simply be static. You can't train it and then code it into the machine's software, because ground types are *incredibly* variable. EMI is *incredibly* variable. There is no way in hell you can get enough training data to do this perfectly, but you could (and should) ship a good-enough algorithm with the detector.

So you start your detecting with a passable (meaning, as good as current detectors) handling algorithm, but a processor on the detector (or your mobile phone, paired to the detector) then continually modifies, in near-real-time, a ground and EMI handling algorithm to be used in that session. So as you detect, the detector gets better and better at handling the ground and EMI characteristics of that area.

I'm not sure what would need to happen to modify this algorithm, I don't know this area of computer science.

My vision for such a detector would be pretty simply, hardware-wise. A phone connects (via Apple lightning or USB cable - bluetooth is too slow) to the detector. All processing happens on the phone. The detector has a battery which powers both the coil and the phone. A hardware interface on the detector handles the analog-to-digital conversion of the coil response, data transfer to and from the phone, and digital-to-analog conversion of the audio output (along with a headphone output).

The phone screen is used to change settings and get visual feedback from the detector (something that is sorely missing on current detectors). A real-time waveform display would be excellent. Imagine, detector operators, that you can see an oscilloscope type view of the raw coil data alongside processed audio waveform, in real-time. You hear the response, and see it. How incredibly useful would that be! Imagine almost infinitely fine variability of all parameters. Imagine custom timings. Regular, over-the-air software updates for the phone app and firmware updates for the detector hardware.

I believe that the company who does this first will make bank if it is implemented well.

Edit: I'm aware of Air Metal Detectors, a kickstarter project which seemed very promising at the start but seems to have flopped. It uses a phone for the processing as I suggested, but I don't think it uses AI or anything fancy internally. Just standard VLF processing.

My favourite gold-related YouTube channel is WilTube Prospecting. Young lad, not sure if he's even a teenager yet. Give him a follow!

It’s not like the infection is a binary thing; you can have a small viral load or a substantial load. There are also many known genetic variants of the virus. Its very well established that vaccinated individuals are affected less than unvaccinated (the vaccine works). 
 

Back on topic:

I’ve noticed American users are clambering for DD coils, especially small ones. Over here in Australia, I don’t see so much use for a small DD coil, except for near EMI sources, despite our ground being far hotter than yours (as far as I know at least). I’d rather user a small mono any day if the week.
 

Why do you USA-based operators want small DD coils over small monos?

On 6/30/2022 at 8:50 AM, midalake said:

Chinese talents??? That might be a little overreach. Most everything coming out of China is inferior.

China is capable of manufacturing extremely cheap and low quality products as well as products made to the absolute highest standards possible on this planet. You get what you pay for, just like anywhere else.

On 7/15/2022 at 7:36 AM, Jonathan Porter said:

Caught the damn thing end of May and am still not right (triple vaxxed), cough lasted for ages, but the two biggest things are the damn brain fog (no joke) and fatigue which are still ongoing! Just got back from a prospecting trip away and the first 3 days were hell till I learned to pace myself.

I have never in my life had to stand on a mild hillside and recover my strength to walk back to the buggy with only a mildly elevated heart rate (90 or so BPM, but felt like 200!!!!). Start of the day things were fine but soon learnt to keep the heart rate down, but boy oh boy after an easy going 5 hours detecting the walk back was a chore!! I improved after 5 or 6 days but still have to be careful!!

Next person who tells me it’s just the effing FLU is going to get a JP style ground balancing!!! 😡 

It is serious bloody business. I got it in March 2020, right at the start. For months after, I couldn't walk up a flight of stairs without needing to stop for a breath. I'm not some super-fit athlete but I'm young and in good shape. Very humbling to get knocked about like that from a bug.

Unfortunately for us consumers, when oil goes up the price for fuel increases immediately, but when it falls, the fuel companies only verrrryyyy sllllooowwwyyy reduce the price at the pumps. Oh well, not much we can do about that.