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After the humidity of Townsville, the dry heat of Mount Isa’s 36 degrees was a welcome change. We arrived in Mount Isa early ready to undertake our fourth FatigueM8 installation, rather fittingly as it happens into a massive Quad Trailer road train, operated as one of 50 by Wagner’s Mount Isa operation that was our 4th installation.

These units really are road trains, with a length well over 50 Meters and weighting north of 120 tonnes, these beasts run 24 hours a day, 7 days a week.

Noting that Mount Isa is at least a five (5) hour plane trip from our base in Canberra and leveraging our software quality assurance heritage after landing, we went through a final set of tests before heading out to site to complete the installation. A couple of tweaks and we were on our way.

Once on-site the installation process is pretty straight forward and took just shy of two (2) hours to complete. The end result is in one way, quite underwhelming, as the steering wheel cover just blends into the wheel and part from the coloured zip it’s hardly noticeable. The zip is a recent addition to the steering wheel cover and simplifies the installation (whilst not annoying the driver). The inclusion of the zip takes roughly an hour out of the installation time. We are interested to see how the zip based unit performs and what our drivers think of it, so watch this space.

The compute unit also blends in somewhat. The dashboard of the T659’s is quite a bit steer than the other trucks we’ve installed in and the result is that the compute unit is somewhat hidden. This isn’t a bad thing, in our original design back in 2018 we’d envisaged the compute unit being a black box hidden somewhere in the truck. Luckily the design of our front camera module is such that it was able to be adjusted to the perfect angle (thanks to our previous trial feedback). 

The truck we installed the unit into was in for a service and I was relieved to see data starting to flow from the unit the next morning (albeit from the truck moving around the yard). This truck, and all the other rigs in Mount Isa run in a 24 hour operation, so we’re excited to see more data flowing in once it hits the road post service. 

Next week we’re off to QLD installing more units, so be sure to check in again to see where we’ve been.

 
Stay save until next time.

This week’s FatigueM8 Friday comes to you following a trip to far North Queensland. Augmented-Intelligence (makers of FatigueM8) were part of a event held at the Smart Precinit  North Queensland (SPNQ) created by our partners KJR Australia. The event titled “Event: How AI is Advancing Workplace Health and Safety” saw presenters from James Cook University, Sparta Science, Cernova  Neuroscience and Augmented-Intelligence share their insights and research findings related to Artificial Intelligence (AI) and Machine Learning (ML).

The performance of athletes and employees have more physical indicators in common than we might expect. So how can technology that has traditionally been used to monitor athlete health and performance be transferred to employees across a range of industries to ensure their health and safety?

The event was created to coincide with Far North Queensland hosing the 2020 edition of the Womens National Basketball League (WNBL). KJR Australia is a proud sponsor of the University of Canberra Capitals (UC Caps) and managed to find a four (4) day gap in their hectic schedule to co-host the event.

Our co-founder Andrew had dual hat’s on for the day, representing both KJR Australia and Augmented-Intelligence. The event gained significant media attention with the ABC interviewing Dr, Richard Franklin from James Cook University and WIN News interviewing Andrew. The news story aired on the nightly news around Queensland.

The full event recording will be available soon (watch this space).

You maybe wondering how FatigueM8 is connected with the AI and workplace health and safety? Well, our FatigueM8 system uses Artificial Intelligence (AI) and Machine Learning (ML) to analyse the Electrocardiograph (ECG) observations recorded from our drivers. After collecting the samples, which are continually recored when ever the driver has two hands on the steering wheel, looking for signs of Fatigue firstly and secondly looking for signs of other cardiovascular disease or abnormalities. The ECG equipment we use at the core of our system is hospital grade, FDA approved ECG and that allows for detailed analysis of the samples. After the installation of the FatigueM8 system we set the system into Baseline mode and observe the drivers. Once the baseline is created, we’ll then start to assess the drivers physiological state and actively alert if we detect, or predict a fatigue event based on the ECG observations.

Watch out for the next installment where we head from Townsville 900kms inland to Mount Isa to commission our 4th FatigueM8 unit, quite fittingly into a Quad Trailer road train! 

Until next time, stay safe.

It’s offical now, Augmented-Intelligence was awarded one of the ACT Government’s Innovation Grants (ICON) as part of the most recent round. The Grant will be used to further our product trials and build out the FatigueM8 portal.

The ICON Grant, along with matched contributions from Augmented-Intelligence and our partners will see close to $100k invested into our project “Fatigue and cardiovascular monitoring for heavy vehicle drivers using an ECG monitor embedded in the steering wheel.”.

The ICON Grants rounds are always very competitive and we are ever so thankful to the the ACT Government and CBR Innovation for support of our journey. We’ll be putting the collective funds to good use, purchasing the hardware to create an additional five (5) FatigueM8 units. The additional units will allow our current trial plans to be doubled from five (5) to ten (10) vehicles, with potential for up to 20 drivers to participate.

As well as the additional units, we’ll also be creating a FatigueM8 portal, where our drivers will be able to login and review their data in an easy to use manner. Watch this space for further developments.

You can read the official press release here

This week we welcome into the FatigueM8 team, Katie Speer, who’s a Ph. D Candidate at the University of Canberra (UC). Katie is studying within the Department of Sport & Exercise Science, Faculty of Health and has published several research papers investigating Heart Rate Variability (HRV) in connection with the autonomic nervous system, maternal exercise influence on childhood HRV and also investigated the ability of commercially available devices to measure HRV in children. All of her papers are available via the link below.

https://www.researchgate.net/profile/Kathryn_Speer

Katie joins the FatigueM8 team for a five (5) month internship to undertake a research project titled “The Validation of the FatigueM8 System for using heart rate variability to detect truck driver fatigue”. Katie will be supported by UC Associate Professor Andrew Mc Kune. The FatigueM8 team was introduced to Professor Mc Kune as we researched the potential cause of HRV observations we’d captured after a trip to Threadbo mountain biking.

Read that post here (http://www.augmented-intelligence.com.au/wp-admin/post.php?post=181)

Professor Mc Kune was a review on the paper we referenced here (doi: 10.3389/fphys.2017.00301) and noting he was a local Canberrian we reached out.

Professor Mc Kune’s “interests include investigating bioenergetic and stress responses (inflammation, autonomic nervous system, HPA-axis) in chronic disease. How do exercise and/or nutrition interventions impact these systems to prevent and treat chronic disease? Methodologies include heart rate variability, salivary bioscience, cardiopulmonary exercise testing, telomere length and ultrasound.”

We’re super excited to have Katie and Andrew onboard; as part of the project they’ll be undertaking we’re going to be expanding our in-cab trials and data collection.

Watch this space for some exciting announcements over the coming weeks.

A couple of Friday’s have past since the last post, but it’s not because of a lack of activity on our side. We been busily working away to grow out our capability. One of the initial features that we had in mind from the outset of FatigueM8, was to add context to the ECG observations by overlaying additional information sets. This week we’ve brought online an additional data stream, leveraging AWS Rekognition service.

As we have explored in previous posts, we’ve had our fair share of challenges with our forward facing camera. Adding in the Rekognition classifications threw up a couple more curve balls to us. The pictures below are from two (2) of our trucks were the FatigueM8 unit had shifted since being installed. Being prototypes we’d used “suckers” to connect the unit to the wind screen and with the changing of temperatures the suction was lost resulting the cameras pointing every which way.

A quick trip to the local hardware store has us back up and pointing in the right direction! A little 25 cms elastic strap and a couple of cable ties have the install back on track.

The resulting photos (below) are back to being captured correctly and ready for processing through rekognitition. Now when an image is uploaded from the truck into the cloud it’s classified by rekognition and then depending on what’s been found, boxes are drawn around the objects.

If a person is detected in the image, we’ll blur them out or don’t use the image just to be safe.

As we run all the images through this process we’ll be able to build up a picture (no pun intended) about the traffic, road and environmental conditions our drivers are driving in; and this will add more context to the ECG observations we collecting.

Until next time, stay safe.

To kick off this week’s edition we start with a nice time series set of images captured from one of our units based in Canberra. On Thursday morning Canberra awoke to a thunderstorm and in this set of images (which span 7 minutes) you can see the rain falling and then freezing on the bonnet of the truck.

This week saw the commissioning of a new FatigueM8 unit, into one of Multiquip’s Kenworth T408 SAR’s, which is setup pulling a B-Double between Marulan and several locations in Sydney.

It’s the first installation into a T408, which is an older model Kenworth (circa 2009/10), fortunately we’d been working with steering wheel in our lab which was the same model as is installed in the T408.

The installation was straight forward and with the steering wheel cover installed powered it up for testing. We observed the ECG monitor “cycling” through the start up sequence over and over again. When measured the electrical current coming through the steering column we noticed some variance in the electrical current. The voltage appears to be bouncing between 11.5 volts and up to 14.5 volts; our ECG monitor operates up to 13.2 volts before switching off to protect the electrical circuit.

In the spirit of rapid prototyping, we setup a voltage regulator in the lab, with the aim of providing a stable 12 volts to the ECG unit. We assembled a linear voltage regulator (below) which was able to drop the power by at least ~1 volt.

We attached the regulator to the T408’s horn cover (pictured below) and set about testing our theory.

We had some success with the voltage regulator in place, the ECG unit powered up and connected to the FatigueM8 on-board unit. We were able to capture the ECG signal for a period of time, before it shutdown and disconnected. We tested all the connections and power supplies and all appeared/reported working at the expected voltage. Our investigations are continuing, watch this space for the next update!

On the positive side, we’re starting to collect data from the front camera and GPS which will be fed into our models.

Until next time, stay safe.

On Wednesday this week I had the opportunity to present our Augmented-Intelligence story to the AWS Canberra User group (Amazon Web Services). It was great chance to reflect on our journey thus far, revisiting the promises and commitments we made to the Australian Trucking community at the 2018 FatigueHACK.

From the beginning, leveraging the cloud (and AWS) were front of mind. As I flicked through the official photos from the event I came across this one (below) from about midway through the first day. AWS Greengrass and AWS Sagemaker are called out as part of the solution; as it happens both of these products are still in the roadmap, but not yet implemented.

But that’s enough of the past, let’s look at what we have currently implemented. The picture below appeared in our presentation and I’ve marked up what we have currently implemented and being uploaded into AWS in the cloud.

We have three (3) FatigueM8 units installed and commissioned, and in each we are capturing the drivers ECG observations, the view out the front wind screen and geocoding each of the observations. From these we’re able to derive vehicle speed, distance travelled, driving time, road conditions, traffic conditions, drivers Heart Rate and a whole host of other statistics.

In my presentation from Wednesday night drilled into all of these areas, highlighting the how we leverage the various AWS Services (AWS S3, AWS Lambda, AWS Anthea and AWS QuickSight) to capture, store, analyse and present the data that we feed into our models to calculate the FatigueM8 Fatigue Score (aka FFS).

Wednesday’s presentation was recorded and is now available to be watched (or re-watched) via the following link. The FatigueM8 overview starts about 17 mins into the recording. You can check out the presentation here https://www.twitch.tv/videos/659965587

Looking back, we promised to spend the prize money on research (and not beer) which we’ve done; oh boy did we stretch that $6k a loooonnnnngggg way. We committed to continue to repay generosity shown to us during the competition, provide objective data (eg ECG recordings) to contribute to a better understanding of how fatigue effects individuals and to help everyone “keep on trucking” in a healthy and sustainable manner.

As for the sky being the limit, well being born in the cloud does have it’s advantages, but its important that we remain focused on supporting those who’s hands are on the steering wheel and feet firmly on the pedals!

Until next week, stay safe.

Our FatigueM8 dataset is continually expanding with several vehicles based in Canberra. Each FatigueM8 unit is fitted with a GPS and each of the artefacts we capture (ECG, Steering wheel movement and front facing camera images) or create (ECG Analysis, vehicle Telemetric’s) is geotagged to add extra depth to our analysis. The images displayed (below) plot the on the map the position of the vehicle when the driver had 2-hands on the steering wheel and FatigueM8 was able to capture a valid ECG signal.

An example of a valid ECG segment captured whilst driving is shown below, along with the heart beat wave form commonly referred too as the QRS Complex.

In the example (above), the R-peak is clearly visible throughout the 10 second sample. The valid sample was collected here (see below) and whilst the car was travelling at 86 kms per hour (in a 90 kms p/hr speed zone). The view out the front of the vehicle was captured, with the traffic conditions being quite light and getting closer to sunset.

Below is an example of an invalid ECG signal, captured just 12 seconds later and as can be clearly seen, there is a mix of R-Peaks, as well as high and low signals. In this 10 second snippet there is not enough R-Peaks identifiable to make any calculations or useful observations in relation to heart rate variation.

The sharp variances up and down correspond to the driver having 2 hands, then 1 hand on the wheel. When we add some more context to the ECG signal from the GPS and front facing camera image, we get more an understanding of what may have happened. One possible scenario would be based on the front facing camera showing the vehicle has changed lanes, which if done correctly would have meant the driver took a hand off the steering wheel to put an indicator on and then switch it off again.

Now back to the pattern. By plotting the location of the valid ECG snippet collections onto the a map (as per the image below), we saw that a high proportion of the samples have been collected on Canberra’s main arterial roads.

We have a couple of hypothesis around why this is the case and we’ll explore them more over the coming weeks.

Until next time, stay safe.

It’s no secret that fatigue is one to the top three (3) killers on our roads in general. However when it comes to fatal heavy vehicle accidents in 2019, fatigue was the largest cause (at 35%) reported in the NTi Major Accident Report 2020.

Crunching the numbers, sadly 50 drivers lost their lives during 2019 and fatigue was responsible for 18 (or 35%) of the 50 lives lost.

The NTi also found that 9% of fatal accidents were caused by a Medical Events, and these events were almost always caused by drivers suffering heart attacks whilst driving. That means that in 2019, 5 drivers lost their lives to cardiovascular related diseases.

These are quite sobering numbers indeed. Fortunately, the trucking industry as a whole has long recognised the need to reduce to 0 the lives lost on our roads; and through the sadness of the lives already lost, there is hope and positivity that together we’ll be able to make sure every drivers gets home safely.

I’ve included a link to the NTi’s report if you’d like to drill into the details and other non-fatigue related findings.

https://ntarc.nationaltransportinsurance.com.au/#introduction

Until next time, stay safe.