smart parking systems, traffic congestion, passenger counting technologies

Transportation IOT: Keeping our roads safe

By: Nick Koiza

Head of Security Business

20th October 2020

4 minute read

Home » Plextek

As we all start moving around our transport systems again, I am reminded almost daily by the risks and safety concerns linked to our congested road systems.

I have a vision that the public should be able to travel easily without worrying about safety on the roads. Aside from education, vehicle servicing, and standard infrastructure maintenance, I believe IoT technologies will significantly enhance the safety of our public whilst they use our road networks. The transportation industry is a huge investor in the Industrial Internet of Things (IIoT), spending approximately $78 billion from 2016-2018. Safety is a part of ‘Transportation IOT’ that is vital for overall success.

In this blog, I list what I consider to be the top 5 areas of transport safety that can be enhanced by IoT technologies:

 

  1. Real-Time Data & AI:

Knowing when to avoid congested or high-risk areas seems simple, but avoidance is the first step to reducing safety risk.  Real-time data utilising AI can be powerful together with IoT technologies. With analytics that can facilitate increased intelligence, we are enabled to make enhanced decision making at both a central or individual level.

Data can come from a huge range of sources. ‘Connected parking’ data can include smart parking systems like the one we helped to develop in Moscow which supports a better flow of vehicles around an urban environment. Interestingly, smart street lighting utilises real-time data to assess when it is dark enough to switch lights on, providing a safer environment. But also these lights could be used in the future as a ‘hub’ for collecting other data like pollution, traffic, and other data.  That combined use of IoT and AI for our network and its surroundings is in its infancy but watch this space.

One of our clients, CNI Guard uses an underground system with environmental sensors to monitor infrastructure. The system prevents and mitigates the risk of gas explosions, stray voltage, flooding, and other breaches of safety, environmental, and quality control regulation. What would have previously taken an accident (ie a manhole explosion) and then a team of people to manually close the road and assess, IoT has enabled automation and risk prevention rather than remediation.

 

  1. Intelligent Transportation Routes

People often use routes they are used to, or ‘the well-trodden path’ instead of the more efficient route. As our Head of Innovation, Alan Cucknell, observed, “people easily fall into routines. When the horrific 7/7 London bombings happened, millions of people were forced to change their usual commuter route. This is a massive behavioural change to observe and interestingly, many people never went back to their previous route. Familiar is not always the best route and smart transport options can find the optimal route, not the route that people are used to”. Innovation in transport can include technology to enable people to make better and safer transport choices, including Public Transit management. At a very basic level, a potential passenger can use a digital display to see how long before their bus/tram arrives. During Covid, more passenger counting technologies are being invested in. These technologies can help companies assess whether their networks are getting congested and unsafe. On a more personalised level, each traveller could use a combination of geofencing, AI, and other smart route tools to enable a personalised, low risk, and quick route.

 

  1. Intelligence on Driver Behaviour

Human error is hard to prevent. How do you incentivise drivers to be more careful, when laws and signage has a limited effect? Our sister company, Redtail Telematics, collects precise, high-resolution data from onboard devices and apps about driver behaviour. This enables insurance companies to offer premiums based on real rather than perceived risk. This can in turn encourage drivers to be more careful on the roads, with rewards related to their behaviour, and subsequently reduced premiums.

When talking to my colleague Andrew Little, of Redtail about whether the technology actually makes a difference on the street, Andrew states: “‘The first six-12 months of a driving career are statistically the most risky. With insight into driving behaviours that can be improved, lives can be, and indeed have been, saved”.

For commercial companies, Vehicle Asset Management (VAM) products provide certainty that vehicles are being driven well, running efficiently, and are where they are supposed to be. This gives fleet managers greater visibility and information to extract further performance from their fleet, which in turn reduces costs as well as safety/operational risk.

Automotive OEMs are increasingly invested in Connected vehicle data (incl. driver behaviours) via conduit platforms to support the road safety agenda.

 

  1. Smart Logistics:

Smart logistics make supply chains more efficient and safer.  Using Intelligent software to identify weak spots in a supply chain can alleviate dangers in transit.

A company, still in the concept stage, I am excited about is Celsius Dynamics which is a logistics solution for cold chain distribution services. Using proprietary algorithms, their smart, digital platform looks at the cold chain process from the manufacturer through to all sequences of temperature-controlled environments.   This level of automation and intelligence theoretically means you can avoid temperature-related explosions in transit, driver tiredness/safety, and ultimately the customer receives a better quality product upon delivery. 

Smart logistics, combined with connected vehicle data is a powerful tool for companies.

 

  1. Autonomous Vehicles & Smart Roads

I believe we need to be very careful about how we implement autonomous vehicles on our roads to ensure that all road users are safer than before this development.   Ensuring the strictest onboard safety standards are adhered to, combined with ‘Smart Street Furniture’ is key.  Practical object and vehicle recognition in intelligent and autonomous transport systems remain a data-first problem.  The de-risking exercise involves testing and validation using real-life scenarios in a controlled environment. The health of the decisions taken by the vehicles on-board systems needs to be validated by external sources of information on our roads.  The more unique data that is captured and identified, the more accurate the decision models can be.

Here in the UK, we have started to invest in Smart Roads, but there is a lot of misunderstanding about what a true Smart Road is with many believing the focus is on speed control which is only part of the puzzle.   Cranfield University’s work on project HumanDrive is an exciting development.

Conclusion:

The transportation industry is making great strides in its evolution, and I am so proud that security technologies can enable individuals and companies to be safer using our transport network. This topic is close to my heart so if you have any developments you think I should know about, please get in touch for a chat: Nicholas.koiza@plextek.com.

As we all start moving around our transport systems again, I am reminded almost daily by the risks and safety concerns linked to our congested road systems.

I have a vision that the public should be able to travel easily without worrying about safety on the roads. Aside from education, vehicle servicing, and standard infrastructure maintenance, I believe IoT technologies will significantly enhance the safety of our public whilst they use our road networks. The transportation industry is a huge investor in the Industrial Internet of Things (IIoT), spending approximately $78 billion from 2016-2018. Safety is a part of ‘Transportation IOT’ that is vital for overall success.

In this blog, I list what I consider to be the top 5 areas of transport safety that can be enhanced by IoT technologies:

 

  1. Real-Time Data & AI:

Knowing when to avoid congested or high-risk areas seems simple, but avoidance is the first step to reducing safety risk.  Real-time data utilising AI can be powerful together with IoT technologies. With analytics that can facilitate increased intelligence, we are enabled to make enhanced decision making at both a central or individual level.

Data can come from a huge range of sources. ‘Connected parking’ data can include smart parking systems like the one we helped to develop in Moscow which supports a better flow of vehicles around an urban environment. Interestingly, smart street lighting utilises real-time data to assess when it is dark enough to switch lights on, providing a safer environment. But also these lights could be used in the future as a ‘hub’ for collecting other data like pollution, traffic, and other data.  That combined use of IoT and AI for our network and its surroundings is in its infancy but watch this space.

One of our clients, CNI Guard uses an underground system with environmental sensors to monitor infrastructure. The system prevents and mitigates the risk of gas explosions, stray voltage, flooding, and other breaches of safety, environmental, and quality control regulation. What would have previously taken an accident (ie a manhole explosion) and then a team of people to manually close the road and assess, IoT has enabled automation and risk prevention rather than remediation.

 

  1. Intelligent Transportation Routes

People often use routes they are used to, or ‘the well-trodden path’ instead of the more efficient route. As our Head of Innovation, Alan Cucknell, observed, “people easily fall into routines. When the horrific 7/7 London bombings happened, millions of people were forced to change their usual commuter route. This is a massive behavioural change to observe and interestingly, many people never went back to their previous route. Familiar is not always the best route and smart transport options can find the optimal route, not the route that people are used to”. Innovation in transport can include technology to enable people to make better and safer transport choices, including Public Transit management. At a very basic level, a potential passenger can use a digital display to see how long before their bus/tram arrives. During Covid, more passenger counting technologies are being invested in. These technologies can help companies assess whether their networks are getting congested and unsafe. On a more personalised level, each traveller could use a combination of geofencing, AI, and other smart route tools to enable a personalised, low risk, and quick route.

 

  1. Intelligence on Driver Behaviour

Human error is hard to prevent. How do you incentivise drivers to be more careful, when laws and signage has a limited effect? Our sister company, Redtail Telematics, collects precise, high-resolution data from onboard devices and apps about driver behaviour. This enables insurance companies to offer premiums based on real rather than perceived risk. This can in turn encourage drivers to be more careful on the roads, with rewards related to their behaviour, and subsequently reduced premiums.

When talking to my colleague Andrew Little, of Redtail about whether the technology actually makes a difference on the street, Andrew states: “‘The first six-12 months of a driving career are statistically the most risky. With insight into driving behaviours that can be improved, lives can be, and indeed have been, saved”.

For commercial companies, Vehicle Asset Management (VAM) products provide certainty that vehicles are being driven well, running efficiently, and are where they are supposed to be. This gives fleet managers greater visibility and information to extract further performance from their fleet, which in turn reduces costs as well as safety/operational risk.

Automotive OEMs are increasingly invested in Connected vehicle data (incl. driver behaviours) via conduit platforms to support the road safety agenda.

 

  1. Smart Logistics:

Smart logistics make supply chains more efficient and safer.  Using Intelligent software to identify weak spots in a supply chain can alleviate dangers in transit.

A company, still in the concept stage, I am excited about is Celsius Dynamics which is a logistics solution for cold chain distribution services. Using proprietary algorithms, their smart, digital platform looks at the cold chain process from the manufacturer through to all sequences of temperature-controlled environments.   This level of automation and intelligence theoretically means you can avoid temperature-related explosions in transit, driver tiredness/safety, and ultimately the customer receives a better quality product upon delivery. 

Smart logistics, combined with connected vehicle data is a powerful tool for companies.

 

  1. Autonomous Vehicles & Smart Roads

I believe we need to be very careful about how we implement autonomous vehicles on our roads to ensure that all road users are safer than before this development.   Ensuring the strictest onboard safety standards are adhered to, combined with ‘Smart Street Furniture’ is key.  Practical object and vehicle recognition in intelligent and autonomous transport systems remain a data-first problem.  The de-risking exercise involves testing and validation using real-life scenarios in a controlled environment. The health of the decisions taken by the vehicles on-board systems needs to be validated by external sources of information on our roads.  The more unique data that is captured and identified, the more accurate the decision models can be.

Here in the UK, we have started to invest in Smart Roads, but there is a lot of misunderstanding about what a true Smart Road is with many believing the focus is on speed control which is only part of the puzzle.   Cranfield University’s work on project HumanDrive is an exciting development.

Conclusion:

The transportation industry is making great strides in its evolution, and I am so proud that security technologies can enable individuals and companies to be safer using our transport network. This topic is close to my heart so if you have any developments you think I should know about, please get in touch for a chat: Nicholas.koiza@plextek.com.

Process Optimisation, business growth, product development, business improvement practices, engineering solutions, creativity?

Can Trump rapidly deploy his ‘miracle cure’?

By: Nigel Whittle

Head of Medical & Healthcare

9th October 2020

3 minute read

Home » Plextek

Last Friday Donald Trump was treated with an antibody cocktail made by the biotech company Regeneron. His recovery has prompted him to call for the drug to be made available to all US citizens through an Emergency Use Authorization. However, the safety and effectiveness of the drug have not yet been proven, and there is no way for the President or his doctors to know that the drug had any effect as most people recover from COVID-19.

As the Metro states today: “Trump is just one of 10 people receiving the drug, which is still in the experimental phase and is intended to boost antibodies to fight the infection”. Is it logistically possible to fulfil Trump’s statement and take a drug from small scale testing to Nationwide rollout? In this blog, we unravel a bit of the situation.

What are the options?

There are over 70 different antibody treatments for COVID-19 currently under investigation. In contrast to convalescent serum, monoclonal antibodies (in this case a pair of antibodies developed by Regeneron) are targeted precisely at the spike protein of SARS-CoV-2. This approach makes good scientific sense and there are real hopes that it will be effective. Already several groups have published data showing that this biologic treatment can reduce the virus load in the body as well as the time it takes for patients to recover. However, the evidence in patients is very limited and these treatments are still classed as experimental drugs while clinical trials are ongoing.

Biologic Drugs

The development of these types of novel biologics starts with the creation of cells that produce therapeutic antibodies. Through the process of cell expansion, sufficient quantities of cells are then manufactured to supply enough antibodies for testing and support of Phase 2 and 3 clinical trials.

How to scale up?

There are significant challenges with rolling out new biologic drugs, aside from the obvious health risks. Rapidly manufacturing medicine requires physical infrastructure in laboratories, supportive mechanics, bioreactor vessels, filling, packaging and a distribution method.

Stephen Guy, Principal Consultant for Life Sciences states, “Both flask-based and bioreactor technologies are commonly employed for cell expansion, and often the choice depends on the type of cells used. Either way, the physical task of ramping up the production process needs many multiples of any technology and a laboratory supplier list that can fulfill requirements.”

In partnership with Design Momentum, we have been exploring the technology behind new collaborative robots that can automate and semi-automate many of the manual processes presently involved in cell expansion. In addition to speeding up laboratory processes, the robots will remove the difficulties of manually handling heavy consumables during seeding and harvesting. Antibody medicines are exciting in their potential to create novel therapeutics and we are keen to support this endeavour with our innovative technology.

What’s next?

As others have noted, there is a strong argument that it is both bad medicine and bad ethics to give unproven drugs to influential people, when they have not been through appropriate randomised clinical trials. Already people are contacting Regeneron asking to be included in the clinical trials of the drug, and it will be very hard for the FDA to resist calls to fast-track the drug into widespread use. It is worth noting that the Trump administration and Regeneron recently agreed to a $450 million deal to manufacture the drug for public use if Regeneron can get either emergency or full FDA approval.

It is easy to express a desire for something to be done, but the hard work is in the implementation. Investment in new laboratory techniques is required to enable efficient deployment to the general public at scale and within timeframes set by our politicians.

Last Friday Donald Trump was treated with an antibody cocktail made by the biotech company Regeneron. His recovery has prompted him to call for the drug to be made available to all US citizens through an Emergency Use Authorization. However, the safety and effectiveness of the drug have not yet been proven, and there is no way for the President or his doctors to know that the drug had any effect as most people recover from COVID-19.

As the Metro states today: “Trump is just one of 10 people receiving the drug, which is still in the experimental phase and is intended to boost antibodies to fight the infection”. Is it logistically possible to fulfil Trump’s statement and take a drug from small scale testing to Nationwide rollout? In this blog, we unravel a bit of the situation.

What are the options?

There are over 70 different antibody treatments for COVID-19 currently under investigation. In contrast to convalescent serum, monoclonal antibodies (in this case a pair of antibodies developed by Regeneron) are targeted precisely at the spike protein of SARS-CoV-2. This approach makes good scientific sense and there are real hopes that it will be effective. Already several groups have published data showing that this biologic treatment can reduce the virus load in the body as well as the time it takes for patients to recover. However, the evidence in patients is very limited and these treatments are still classed as experimental drugs while clinical trials are ongoing.

Biologic Drugs

The development of these types of novel biologics starts with the creation of cells that produce therapeutic antibodies. Through the process of cell expansion, sufficient quantities of cells are then manufactured to supply enough antibodies for testing and support of Phase 2 and 3 clinical trials.

How to scale up?

There are significant challenges with rolling out new biologic drugs, aside from the obvious health risks. Rapidly manufacturing medicine requires physical infrastructure in laboratories, supportive mechanics, bioreactor vessels, filling, packaging and a distribution method.

Stephen Guy, Principal Consultant for Life Sciences states, “Both flask-based and bioreactor technologies are commonly employed for cell expansion, and often the choice depends on the type of cells used. Either way, the physical task of ramping up the production process needs many multiples of any technology and a laboratory supplier list that can fulfill requirements.”

In partnership with Design Momentum, we have been exploring the technology behind new collaborative robots that can automate and semi-automate many of the manual processes presently involved in cell expansion. In addition to speeding up laboratory processes, the robots will remove the difficulties of manually handling heavy consumables during seeding and harvesting. Antibody medicines are exciting in their potential to create novel therapeutics and we are keen to support this endeavour with our innovative technology.

What’s next?

As others have noted, there is a strong argument that it is both bad medicine and bad ethics to give unproven drugs to influential people, when they have not been through appropriate randomised clinical trials. Already people are contacting Regeneron asking to be included in the clinical trials of the drug, and it will be very hard for the FDA to resist calls to fast-track the drug into widespread use. It is worth noting that the Trump administration and Regeneron recently agreed to a $450 million deal to manufacture the drug for public use if Regeneron can get either emergency or full FDA approval.

It is easy to express a desire for something to be done, but the hard work is in the implementation. Investment in new laboratory techniques is required to enable efficient deployment to the general public at scale and within timeframes set by our politicians.

cutting-edge projects here at Plextek including a number of mm-wave designs.

The mm-Wave Antenna Approach

By: James Henderson

Senior Consultant, Antennas & Propagation

25th September 2020

6 minute read

Home » Plextek

Over the past eight years of my career, I’ve been fortunate enough to work on several different cutting-edge projects here at Plextek including a number of mm-wave designs. These have included both research programmes and product development, covering radar sensors, communication systems, and medical applications. This has given me a great depth of experience into different approaches to meet our customer’s specific requirements. Over this time, I have found that one of the most challenging aspects of working in this frequency range is the integration of mm-wave front-end electronics with an optimised antenna solution, to provide an efficient, and controlled radiation pattern.

Whilst there are many different approaches to a mm-wave antenna design, in my experience, by far the most popular choice for mm-wave applications is some variation of the patch antenna. To me, this is because they are both cheap to produce and surprisingly efficient, albeit over a narrow bandwidth. Whilst there are techniques to improve the bandwidth of the patch antenna, I have personally found that they do not necessarily offer the best performance when compared to alternative approaches.

That said, like all decisions in engineering, the best approach depends on what your priorities are and what you are trying to achieve. For highly cost-sensitive applications, it is difficult to justify a more complex and ultimately more expensive approach if an edge-fed patch antenna will meet your requirements.

A rectangular edge-fed patch antenna, as its name implies, is excited with a signal launched from a microstrip transmission line to one edge of the rectangular element (the element being the specific part of the antenna where radiation occurs). The rectangular element, like the microstrip transmission line, is also over a large ground plane with often a thin microwave dielectric between (a thin microwave dielectric is usually required for the mm-wave electronics to provide a low inductance path to ground). This causes the element to resonate at a specific frequency due to its length, dielectric thickness, and dielectric permittivity. Whilst this thin dielectric enables efficient radiation, this only occurs over a narrow range of frequencies resulting in the element bandwidth being a particularly narrow band. To improve the element match, an inset feed can also be used as shown in the pair of patch elements below.

To increase the gain of the antenna, multiple elements can then be added by feeding the next element in series with a short length of microstrip from the far edge of the first, and so on. This works well providing all the elements radiate in phase with respect to each other. To ensure all the elements radiate in phase, a specific length of microstrip should be used for the required frequency. This causes the series-fed array to also provide a narrow array bandwidth as it relies on a specific wavelength which, over frequency, will inevitably change.

To improve the element bandwidth, a stacked patch is a popular choice. Here, stacking a second patch above the first effectively increases the depth of microwave laminate between the top patch and the ground plane, trading a small amount of efficiency for bandwidth. This approach does, however, have a financial cost associated with it, as multiple layers of expensive microwave dielectric are now required.

To improve the array bandwidth, a feed network which provides an equal electrical line length to each element is often required. This can be achieved through a corporate feed network where the transmission line is split as it feeds all the elements with the same length from the source. An example of this is shown in the 4-element via-fed stacked patch array below.

It is often desirable to increase the gain of an antenna generally to improve the system range, whether it be for a communication or radar system. However, a high-gain antenna is not always advantageous as it essentially directs all the energy in a specific direction, but less in others. To use an analogy it’s like squeezing a balloon, a high-gain antenna can be squeezed such that there is one main lobe where most of the signal (or air in the case of the balloon) is going, but the amount of signal in other directions is reduced. This is fine if this is the intended direction, and for fixed point-to-point communication links this is usually the case. However, in a dynamic system where the direction of radiation needs to change rapidly, an electronically steerable solution is usually required.

Electronically steerable antennas are usually realised in the form of an array of separate elements, like the examples discussed above, but by adjusting the phase of the signal radiating from each can cause the direction of peak gain to change. The challenge, particularly at mm-wave frequencies, is the ability to provide the required phase to each element whilst managing the interaction between nearby elements. This is where, in my opinion, achieving good performance with patch elements becomes challenging as, without careful design, the tightly spaced elements and their feed network can interact. This causes the relative phase between elements and the current distribution across the array to be affected, resulting in a less-than-ideal radiation pattern.

An alternative to the patch element is a radiating slot. A slot in an infinite conductor is considered as the complement to a dipole in free space. A patch antenna is often modeled as two slots side-by-side radiating in phase; this results in an increased element gain for the patch over a thin slot element, but reduced beamwidth. Whilst this allows a patch array to achieve a higher total gain for an array with the same number of elements when compared to a slot array, the reduced beamwidth means a patch array cannot steer over as wider a scan angle.

Another advantage I see with using slot elements in an array is the ability to feed them from waveguide rather than microstrip, or similar transmission lines. The signal is constrained within the waveguide which helps to lower coupling between adjacent transmission lines used to feed nearby elements. This inherent isolation of the feed network helps to achieve a more controlled radiation pattern over wide bandwidths and scan angles. Naturally, however, there is a higher cost associated with a waveguide fed slot array antenna as it tends to require a more complex design and manufacturing process. An example of this can be seen below where an 8 x 10-element slot array (with an additional single 10-element array to one side) is fed from substrate-integrated-waveguide. This has been designed directly onto a multilayer PCB which can support the associated RF front-end electronics.

Designing the antenna directly onto the same PCB as the electronics are usually the most cost-effective approach. Not least does this prevent the need for an additional separate antenna but simplifies the assembly process. However, achieving efficient, wideband antenna performance on a PCB which also contains mm-wave electronics can be very challenging. This is because the electronics tend to require contrasting PCB requirements to the antenna, particularly with respect to the thickness of the PCB dielectric as discussed earlier. Our conference paper and presentation at EuCAP 2020 aims to address this fundamental issue for use in substrate-integrated-waveguide (SIW) fed antenna arrays. The approach presented demonstrated a significant reduction in the insertion loss of substrate-integrated-waveguide using a novel feed approach for a multilayer PCB design.

If further improvement in antenna efficiency and bandwidth is required, particularly for high-gain antennas, the use of a sectoral horn could be considered. Horn antennas are a popular choice for microwave and mm-wave applications because they offer good, predictable performance and their operation can be accurately calculated through well-documented equations. The challenge with using a horn antenna for mm-wave applications is generally feeding the signal into each sectoral horn element. An example where Plextek has implemented a sectoral horn array for an mm-wave radar sensor can be seen on Texas Instrument’s website. This short-range sensor was optimised to achieve a wide coverage using TI’s IWR6843 radar-on-chip device.

Whilst the sectoral horn antenna approach can offer improved bandwidth and efficiency for high-gain elements, it does come at a cost both to manufacture, as it requires an additional component, as well as its larger size and weight. The example below is of a 64-element sectoral horn array.

There are many other solutions to mm-wave antennas such as parabolic reflectors, as used in the development of the FOD radar, but the examples explored in this blog are probably the most relevant to consumer electronics both for communication or short-range radar systems.

I hope that this is both interesting and informative, as to me, the antenna choice is vitally important to any mm-wave design as it dictates a considerable amount of the system around it.

Over the past eight years of my career, I’ve been fortunate enough to work on several different cutting-edge projects here at Plextek including a number of mm-wave designs. These have included both research programmes and product development, covering radar sensors, communication systems, and medical applications. This has given me a great depth of experience into different approaches to meet our customer’s specific requirements. Over this time, I have found that one of the most challenging aspects of working in this frequency range is the integration of mm-wave front-end electronics with an optimised antenna solution, to provide an efficient, and controlled radiation pattern.

Whilst there are many different approaches to a mm-wave antenna design, in my experience, by far the most popular choice for mm-wave applications is some variation of the patch antenna. To me, this is because they are both cheap to produce and surprisingly efficient, albeit over a narrow bandwidth. Whilst there are techniques to improve the bandwidth of the patch antenna, I have personally found that they do not necessarily offer the best performance when compared to alternative approaches.

That said, like all decisions in engineering, the best approach depends on what your priorities are and what you are trying to achieve. For highly cost-sensitive applications, it is difficult to justify a more complex and ultimately more expensive approach if an edge-fed patch antenna will meet your requirements.

A rectangular edge-fed patch antenna, as its name implies, is excited with a signal launched from a microstrip transmission line to one edge of the rectangular element (the element being the specific part of the antenna where radiation occurs). The rectangular element, like the microstrip transmission line, is also over a large ground plane with often a thin microwave dielectric between (a thin microwave dielectric is usually required for the mm-wave electronics to provide a low inductance path to ground). This causes the element to resonate at a specific frequency due to its length, dielectric thickness, and dielectric permittivity. Whilst this thin dielectric enables efficient radiation, this only occurs over a narrow range of frequencies resulting in the element bandwidth being a particularly narrow band. To improve the element match, an inset feed can also be used as shown in the pair of patch elements below.

To increase the gain of the antenna, multiple elements can then be added by feeding the next element in series with a short length of microstrip from the far edge of the first, and so on. This works well providing all the elements radiate in phase with respect to each other. To ensure all the elements radiate in phase, a specific length of microstrip should be used for the required frequency. This causes the series-fed array to also provide a narrow array bandwidth as it relies on a specific wavelength which, over frequency, will inevitably change.

To improve the element bandwidth, a stacked patch is a popular choice. Here, stacking a second patch above the first effectively increases the depth of microwave laminate between the top patch and the ground plane, trading a small amount of efficiency for bandwidth. This approach does, however, have a financial cost associated with it, as multiple layers of expensive microwave dielectric are now required.

To improve the array bandwidth, a feed network which provides an equal electrical line length to each element is often required. This can be achieved through a corporate feed network where the transmission line is split as it feeds all the elements with the same length from the source. An example of this is shown in the 4-element via-fed stacked patch array below.

It is often desirable to increase the gain of an antenna generally to improve the system range, whether it be for a communication or radar system. However, a high-gain antenna is not always advantageous as it essentially directs all the energy in a specific direction, but less in others. To use an analogy it’s like squeezing a balloon, a high-gain antenna can be squeezed such that there is one main lobe where most of the signal (or air in the case of the balloon) is going, but the amount of signal in other directions is reduced. This is fine if this is the intended direction, and for fixed point-to-point communication links this is usually the case. However, in a dynamic system where the direction of radiation needs to change rapidly, an electronically steerable solution is usually required.

Electronically steerable antennas are usually realised in the form of an array of separate elements, like the examples discussed above, but by adjusting the phase of the signal radiating from each can cause the direction of peak gain to change. The challenge, particularly at mm-wave frequencies, is the ability to provide the required phase to each element whilst managing the interaction between nearby elements. This is where, in my opinion, achieving good performance with patch elements becomes challenging as, without careful design, the tightly spaced elements and their feed network can interact. This causes the relative phase between elements and the current distribution across the array to be affected, resulting in a less-than-ideal radiation pattern.

An alternative to the patch element is a radiating slot. A slot in an infinite conductor is considered as the complement to a dipole in free space. A patch antenna is often modeled as two slots side-by-side radiating in phase; this results in an increased element gain for the patch over a thin slot element, but reduced beamwidth. Whilst this allows a patch array to achieve a higher total gain for an array with the same number of elements when compared to a slot array, the reduced beamwidth means a patch array cannot steer over as wider a scan angle.

Another advantage I see with using slot elements in an array is the ability to feed them from waveguide rather than microstrip, or similar transmission lines. The signal is constrained within the waveguide which helps to lower coupling between adjacent transmission lines used to feed nearby elements. This inherent isolation of the feed network helps to achieve a more controlled radiation pattern over wide bandwidths and scan angles. Naturally, however, there is a higher cost associated with a waveguide fed slot array antenna as it tends to require a more complex design and manufacturing process. An example of this can be seen below where an 8 x 10-element slot array (with an additional single 10-element array to one side) is fed from substrate-integrated-waveguide. This has been designed directly onto a multilayer PCB which can support the associated RF front-end electronics.

Designing the antenna directly onto the same PCB as the electronics are usually the most cost-effective approach. Not least does this prevent the need for an additional separate antenna but simplifies the assembly process. However, achieving efficient, wideband antenna performance on a PCB which also contains mm-wave electronics can be very challenging. This is because the electronics tend to require contrasting PCB requirements to the antenna, particularly with respect to the thickness of the PCB dielectric as discussed earlier. Our conference paper and presentation at EuCAP 2020 aims to address this fundamental issue for use in substrate-integrated-waveguide (SIW) fed antenna arrays. The approach presented demonstrated a significant reduction in the insertion loss of substrate-integrated-waveguide using a novel feed approach for a multilayer PCB design.

If further improvement in antenna efficiency and bandwidth is required, particularly for high-gain antennas, the use of a sectoral horn could be considered. Horn antennas are a popular choice for microwave and mm-wave applications because they offer good, predictable performance and their operation can be accurately calculated through well-documented equations. The challenge with using a horn antenna for mm-wave applications is generally feeding the signal into each sectoral horn element. An example where Plextek has implemented a sectoral horn array for an mm-wave radar sensor can be seen on Texas Instrument’s website. This short-range sensor was optimised to achieve a wide coverage using TI’s IWR6843 radar-on-chip device.

Whilst the sectoral horn antenna approach can offer improved bandwidth and efficiency for high-gain elements, it does come at a cost both to manufacture, as it requires an additional component, as well as its larger size and weight. The example below is of a 64-element sectoral horn array.

There are many other solutions to mm-wave antennas such as parabolic reflectors, as used in the development of the FOD radar, but the examples explored in this blog are probably the most relevant to consumer electronics both for communication or short-range radar systems.

I hope that this is both interesting and informative, as to me, the antenna choice is vitally important to any mm-wave design as it dictates a considerable amount of the system around it.

Industrial automation

Is 5G the Answer to Connectivity for Industrial IoT?

By: Shahzad Nadeem

Head of Smart Cities

10th Sept 2020

4 minute read

Home » Plextek

As the first cellular network technology designed to support industrial use cases, 5G is billed to become the basis for the Industrial Internet of Things (IIoT) and enabler for Industry 4.0 technologies, such as VR, AR and AI.

Certainly, the promises of super-fast data 5G rates, ultra-low latency and vastly increased network capacity are essential for the high-quality connectivity demands of the industrial sector. But will 5G live up to expectations? What are the challenges and opportunities? And when can we expect to see widespread adoption of the technology?

What is it good for?
Industrial connectivity use cases for 5G range from smart factories with real-time process automation, to wide-area connected products with lifecycle management. To address these different connectivity requirements, businesses currently have to deploy multiple networks. LAN technologies such as Ethernet, Wi-Fi, Zigbee and Lora are used for in-building connectivity, while a combination of LAN and WAN solutions are used for connectivity between buildings and fibre, cellular and satellite handle remote assets.

Wired or wireless?
Existing wireless technologies do not provide the stringent low latency performance required for industrial automation, hence the heavy reliance on wired technologies for time-critical applications. But the deployment flexibility, reduced cost of manufacturing, installation and maintenance, and long-term reliability compared to wired connections, makes wireless technologies very attractive for industrial markets.

So far, cellular connectivity has typically been used only for those use cases that involve mobile assets, such as fleet management and asset tracking. Research by Analysis Mason suggests this is due to a combination of technical and commercial limitations of existing cellular networks. The current quality of connectivity is not sufficient for mission-critical applications, while the cost of the SIM business model presents a barrier to adoption and the public network model is not always considered suitable for an industrial setting.

Promises, promises
5G promises to address the performance-related issues as well as enabling entirely new use cases. The ability to connect and transfer data from up to 1 million sensors per km2, allowing continuous collection of data from vast numbers of sensors, will enable remote monitoring and predictive maintenance of manufacturing assets. Low latency together with edge cloud capabilities will underpin real-time processes such as collaborative robots for process automation, and high reliability will support mission-critical operations.
These can be delivered via private 5G networks, offering a level of control and security comparable to wired networks. However, the development of the 5G standard is not yet complete, with enhancements enabling ultra-reliable low latency communications (uRLCC) yet to arrive, as well as the upgrades to infrastructure needed to offer standalone 5G.

From power gen to remote surgery
The mMTC (Massive Machine Type Communication) and uRLLC capabilities sit at the core of 5G use cases in industry. Some industrial processes demand extremely tight KPIs for communications between controllers and devices. Use cases like power generation and distribution, process automation, motion control and communication between different controls rely heavily on low latency capability.

But there is a host of other use cases that need 5G. Take tactile communications such as remote surgery, health care monitoring, online gaming and synchronised remote music. Then there are autonomous vehicles, drones and robotic applications like sense-and-avoid, automated overtake, collaborative collision avoidance, HDVP (high-density vehicle platooning) and V2X (Vehicle to everything) communications. And high-density communications like smart wearables, connected stadiums and IoT are all other use cases that need 5G to deliver.

Payback
While the challenges are considerable, the potential added value of running industrial use cases on improved connectivity is substantial. A study by Barclays predicted a potential £2 billion increase in annual UK manufacturing revenues by 2025 as a result of 5G implementation. Another recent McKinsey study predicts improved connectivity in manufacturing and other advanced industries could result in $400-650 billion of global GDP impact by 2030.

But despite these predictions, progress towards implementing 5G has been hampered by several issues. With the technology still evolving and the value potential split across use cases in different domains, there are difficulties in justifying the business case and ROI. There are also cultural barriers, because successful 5G deployment in manufacturing relies on multiple players across an ecosystem, from manufacturing engineers to telecoms providers who need to engage and cooperate. There are also concerns around security and ownership of data, as well as compatibility and interoperability with existing systems.

First in the game

There has been a tug of war between mobile network operators across the world to be the first in launching 5G networks. Oreedo, the Qatari mobile operator, was announced as the first 5G network mainly using eMBB capabilities for FWA and demonstrated the use of low altitude drone with 5G. Telecom Italia announced San Marino to be the first European state to provide state wide 5G coverage, bringing together eMBB and mMTC capabilities in the mmWave band. Vodacom group launched Africa’s first 5G capability in the 3.5GHz band for FWA access. Interestingly the South Korean government forced the main three mobile operators -SK Telecom, KT and LG to launch 5G at the same time. China mobile, China Telecom, NTT Docomo, Kddi and Telstra in Asia, were also the first to do mass 5g trails in different cities. Verizon, AT&T, Sprint and T-mobile in USA deployed 5G networks in different bands targeting varied market sectors. Vodafone , Telefonica, Orange and Three mobile have deployed their 5G networks in Europe and there is a lot of emphasis on private 5G networks. It’s a busy marketplace, but there is a difference between launch and full deployment.

Be in it to win it
5G has the potential to offer a strong foundation for IIoT technology and to play a key role in driving the future of Industry 4.0. In time, it may even become the standard wireless technology of choice for industrial connectivity. Although the technology is still evolving, for businesses to stay competitive it is essential that they explore the new possibilities presented by 5G. In addition, to steer future development and ensure that their specific industry needs are met, it is increasingly important that they engage and collaborate across the 5G value chain.

As the first cellular network technology designed to support industrial use cases, 5G is billed to become the basis for the Industrial Internet of Things (IIoT) and enabler for Industry 4.0 technologies, such as VR, AR and AI.

Certainly, the promises of super-fast data 5G rates, ultra-low latency and vastly increased network capacity are essential for the high-quality connectivity demands of the industrial sector. But will 5G live up to expectations? What are the challenges and opportunities? And when can we expect to see widespread adoption of the technology?

What is it good for?
Industrial connectivity use cases for 5G range from smart factories with real-time process automation, to wide-area connected products with lifecycle management. To address these different connectivity requirements, businesses currently have to deploy multiple networks. LAN technologies such as Ethernet, Wi-Fi, Zigbee and Lora are used for in-building connectivity, while a combination of LAN and WAN solutions are used for connectivity between buildings and fibre, cellular and satellite handle remote assets.

Wired or wireless?
Existing wireless technologies do not provide the stringent low latency performance required for industrial automation, hence the heavy reliance on wired technologies for time-critical applications. But the deployment flexibility, reduced cost of manufacturing, installation and maintenance, and long-term reliability compared to wired connections, makes wireless technologies very attractive for industrial markets.

So far, cellular connectivity has typically been used only for those use cases that involve mobile assets, such as fleet management and asset tracking. Research by Analysis Mason suggests this is due to a combination of technical and commercial limitations of existing cellular networks. The current quality of connectivity is not sufficient for mission-critical applications, while the cost of the SIM business model presents a barrier to adoption and the public network model is not always considered suitable for an industrial setting.

Promises, promises
5G promises to address the performance-related issues as well as enabling entirely new use cases. The ability to connect and transfer data from up to 1 million sensors per km2, allowing continuous collection of data from vast numbers of sensors, will enable remote monitoring and predictive maintenance of manufacturing assets. Low latency together with edge cloud capabilities will underpin real-time processes such as collaborative robots for process automation, and high reliability will support mission-critical operations.
These can be delivered via private 5G networks, offering a level of control and security comparable to wired networks. However, the development of the 5G standard is not yet complete, with enhancements enabling ultra-reliable low latency communications (uRLCC) yet to arrive, as well as the upgrades to infrastructure needed to offer standalone 5G.

From power gen to remote surgery
The mMTC (Massive Machine Type Communication) and uRLLC capabilities sit at the core of 5G use cases in industry. Some industrial processes demand extremely tight KPIs for communications between controllers and devices. Use cases like power generation and distribution, process automation, motion control and communication between different controls rely heavily on low latency capability.

But there is a host of other use cases that need 5G. Take tactile communications such as remote surgery, health care monitoring, online gaming and synchronised remote music. Then there are autonomous vehicles, drones and robotic applications like sense-and-avoid, automated overtake, collaborative collision avoidance, HDVP (high-density vehicle platooning) and V2X (Vehicle to everything) communications. And high-density communications like smart wearables, connected stadiums and IoT are all other use cases that need 5G to deliver.

Payback
While the challenges are considerable, the potential added value of running industrial use cases on improved connectivity is substantial. A study by Barclays predicted a potential £2 billion increase in annual UK manufacturing revenues by 2025 as a result of 5G implementation. Another recent McKinsey study predicts improved connectivity in manufacturing and other advanced industries could result in $400-650 billion of global GDP impact by 2030.

But despite these predictions, progress towards implementing 5G has been hampered by several issues. With the technology still evolving and the value potential split across use cases in different domains, there are difficulties in justifying the business case and ROI. There are also cultural barriers, because successful 5G deployment in manufacturing relies on multiple players across an ecosystem, from manufacturing engineers to telecoms providers who need to engage and cooperate. There are also concerns around security and ownership of data, as well as compatibility and interoperability with existing systems.

First in the game

There has been a tug of war between mobile network operators across the world to be the first in launching 5G networks. Oreedo, the Qatari mobile operator, was announced as the first 5G network mainly using eMBB capabilities for FWA and demonstrated the use of low altitude drone with 5G. Telecom Italia announced San Marino to be the first European state to provide state wide 5G coverage, bringing together eMBB and mMTC capabilities in the mmWave band. Vodacom group launched Africa’s first 5G capability in the 3.5GHz band for FWA access. Interestingly the South Korean government forced the main three mobile operators -SK Telecom, KT and LG to launch 5G at the same time. China mobile, China Telecom, NTT Docomo, Kddi and Telstra in Asia, were also the first to do mass 5g trails in different cities. Verizon, AT&T, Sprint and T-mobile in USA deployed 5G networks in different bands targeting varied market sectors. Vodafone , Telefonica, Orange and Three mobile have deployed their 5G networks in Europe and there is a lot of emphasis on private 5G networks. It’s a busy marketplace, but there is a difference between launch and full deployment.

Be in it to win it
5G has the potential to offer a strong foundation for IIoT technology and to play a key role in driving the future of Industry 4.0. In time, it may even become the standard wireless technology of choice for industrial connectivity. Although the technology is still evolving, for businesses to stay competitive it is essential that they explore the new possibilities presented by 5G. In addition, to steer future development and ensure that their specific industry needs are met, it is increasingly important that they engage and collaborate across the 5G value chain.

If you have any questions about how 5G can enhance your technology roadmap, please get in touch for an initial chat.

Technology development, gary numan, robots

Are Friends Electric? Our Future Lives with Robots

By: Nigel Whittle

Head of Medical & Healthcare

26th August 2020

5 minute read

Home » Plextek

The Czech writer Karel Čapek set his play ‘Rossum’s Universal Robots’ in the year 2000, and in his timeline, robots became cheap and widely available, allowing products to be made at one fifth the previous cost[1]. In our universe, robots have become, if not commonplace, at least an accepted feature of the working environment. From the first examples of automated production lines (perhaps most famously in the Nissan car factory) through to robots designed for delicate surgery, we are becoming accustomed to robots having an increasingly prominent role.

Industrial Robotics

There are clearly tasks for which robots, with their strength and their capability for repetitive exact movements, are much better suited than humans, who may be more suited for skilled tasks or tasks that are non-repetitive. For many years, industrial robots were large-scale production systems operating in isolation, carrying out specific actions, without variation and to a high degree of accuracy, determined by software that specified the exact parameters of movement. These traditional industrial robots were anything but user-friendly – despite being fenced off to keep human workers safe, their inflexibility has resulted in occasional industrial accidents, including the death of workers[2].

Recent advances in technology have allowed robotic systems to be scaled down in size and cost, allowing smaller robotic systems to play a more integrated role in environments such as laboratories and other industrial settings. Totally automated solutions, with little human interaction, are still inherently inflexible and can be very expensive. With safety in mind, a preferred option has therefore been isolated islands of automation, perhaps functioning as a specific workstation, operating independently but which can interact to a limited extent with nearby workers.

In some areas, most notably the pharma sector, widespread adoption of automation has been limited due to concerns over safety when staff are interfacing with robotic systems. This has resulted in most automation systems being housed in large protective enclosures that are costly and take-up valuable laboratory space.

Working hand-in-gripper

But imagine a world in which humans and robots collaborate on a specific project, working together within a shared space, building a device together, or conducting complex operations together. This represents a real step-change in the use of robotic systems, as they begin to perform tasks not normally associated with robots, including customer service, construction, cleaning, cooking, or hospitality.

Such robotic systems, commonly referred to as cobots, are being designed to operate in proximity to humans, collaborate with them, and move around independently in their shared workspace. They are still robots but freed from their constraints, and thanks to their small size and mobility, cobots can be deployed in a range of environments.

Apart from the technical issues of developing such a robot, the biggest challenges lie in ensuring the robot interacts effectively with the human, is aware of the actions being undertaken by its partner and operates at a high level of safety. Cobots must be equipped with safety sensors and software, and are often constructed of lightweight materials, with rounded edges, and with limitations on movement range, speed, and force. Ideally, they slow down when a human worker is close to them, and if they bump into somebody, they stop immediately.

As cobots become more collaborative and more interactive, they will require highly reliable proximity and warning systems, that allow them to sense the presence of a human colleague in their immediate proximity and adjust to avoid collisions. This will result from the addition of sensors and enhanced processing power to make cobots smarter. Our Life Science Partnership is already starting to develop simple robotic systems that use complex integrated sensors to detect and interact with nearby workers, enhancing safety and allowing improved co-working.

Further developments are likely to include improved user interfaces to allow for clear-cut interaction, and perhaps user-ID systems to allow interaction with specified individuals.

Machines Like Me

Such systems will be easy to train in new tasks, thanks to machine learning processes whereby the cobot learns to complete a task through repeated interaction within a dynamic environment. This exploration generates data, which can be used by the cobot to identify the best means to complete a task without recourse to human intervention. As the technology develops then AI systems could be introduced to predict actions and suggest improvements in procedures.

There is no doubt that many of the repetitive jobs performed by humans today will be done by robots tomorrow. But, collaborative robotics demonstrates that such tasks can include highly interactive processes that provide a route to combining the skill that humans can bring with the capabilities of robots. This will allow activities to be conducted more effectively whilst creating more challenging and rewarding jobs in the process.


[1] https://en.wikipedia.org/wiki/R.U.R.

[2] https://nypost.com/2015/07/02/robot-kills-man-at-volkswagen-plant/

The Czech writer Karel Čapek set his play ‘Rossum’s Universal Robots’ in the year 2000, and in his timeline, robots became cheap and widely available, allowing products to be made at one fifth the previous cost[1]. In our universe, robots have become, if not commonplace, at least an accepted feature of the working environment. From the first examples of automated production lines (perhaps most famously in the Nissan car factory) through to robots designed for delicate surgery, we are becoming accustomed to robots having an increasingly prominent role.

Industrial Robotics

There are clearly tasks for which robots, with their strength and their capability for repetitive exact movements, are much better suited than humans, who may be more suited for skilled tasks or tasks that are non-repetitive. For many years, industrial robots were large-scale production systems operating in isolation, carrying out specific actions, without variation and to a high degree of accuracy, determined by software that specified the exact parameters of movement. These traditional industrial robots were anything but user-friendly – despite being fenced off to keep human workers safe, their inflexibility has resulted in occasional industrial accidents, including the death of workers[2].

Recent advances in technology have allowed robotic systems to be scaled down in size and cost, allowing smaller robotic systems to play a more integrated role in environments such as laboratories and other industrial settings. Totally automated solutions, with little human interaction, are still inherently inflexible and can be very expensive. With safety in mind, a preferred option has therefore been isolated islands of automation, perhaps functioning as a specific workstation, operating independently but which can interact to a limited extent with nearby workers.

In some areas, most notably the pharma sector, widespread adoption of automation has been limited due to concerns over safety when staff are interfacing with robotic systems. This has resulted in most automation systems being housed in large protective enclosures that are costly and take-up valuable laboratory space.

Working hand-in-gripper

But imagine a world in which humans and robots collaborate on a specific project, working together within a shared space, building a device together, or conducting complex operations together. This represents a real step-change in the use of robotic systems, as they begin to perform tasks not normally associated with robots, including customer service, construction, cleaning, cooking, or hospitality.

Such robotic systems, commonly referred to as cobots, are being designed to operate in proximity to humans, collaborate with them, and move around independently in their shared workspace. They are still robots but freed from their constraints, and thanks to their small size and mobility, cobots can be deployed in a range of environments.

Apart from the technical issues of developing such a robot, the biggest challenges lie in ensuring the robot interacts effectively with the human, is aware of the actions being undertaken by its partner and operates at a high level of safety. Cobots must be equipped with safety sensors and software, and are often constructed of lightweight materials, with rounded edges, and with limitations on movement range, speed, and force. Ideally, they slow down when a human worker is close to them, and if they bump into somebody, they stop immediately.

As cobots become more collaborative and more interactive, they will require highly reliable proximity and warning systems, that allow them to sense the presence of a human colleague in their immediate proximity and adjust to avoid collisions. This will result from the addition of sensors and enhanced processing power to make cobots smarter. Our Life Science Partnership is already starting to develop simple robotic systems that use complex integrated sensors to detect and interact with nearby workers, enhancing safety and allowing improved co-working.

Further developments are likely to include improved user interfaces to allow for clear-cut interaction, and perhaps user-ID systems to allow interaction with specified individuals.

Machines Like Me

Such systems will be easy to train in new tasks, thanks to machine learning processes whereby the cobot learns to complete a task through repeated interaction within a dynamic environment. This exploration generates data, which can be used by the cobot to identify the best means to complete a task without recourse to human intervention. As the technology develops then AI systems could be introduced to predict actions and suggest improvements in procedures.

There is no doubt that many of the repetitive jobs performed by humans today will be done by robots tomorrow. But, collaborative robotics demonstrates that such tasks can include highly interactive processes that provide a route to combining the skill that humans can bring with the capabilities of robots. This will allow activities to be conducted more effectively whilst creating more challenging and rewarding jobs in the process.


[1] https://en.wikipedia.org/wiki/R.U.R.

[2] https://nypost.com/2015/07/02/robot-kills-man-at-volkswagen-plant/