Category: Amberblog

Australia’s top ten patents and their role in innovation

Australia has a long history of innovation, dating back over 50,000 years ago to when the original aborginal inhabitants first learned to use bushfire as a form of farming. Since then Australian innovators have added much to the world, including refrigeration, the torpedo, military tank, electronic pace maker, ultrasound and the black box (even if the ‘black box’ is orange in the figure below).   


In recent years Australia’s committment to innovation has been mixed. However now that our latest mining boom is coming to an end, innovation in other areas besides mining is becoming an increasing part of the national debate.

Australian startup Ambercite is built on innovation, both by developing innovative and world leading software tools that can help mine the global patent database, and also by enabling other companies to innovate via the application of its tools.  Most recently Ambercite has developed Cluster Searching, which can turn anybody with a rudimentary knowledge of patents into an instant world-class patent searcher – by doing the hard work for them. Not suprisingly, Cluster Searching is attracting global interest from some of the world’s leading patent seachers.

Another innovation developed by Ambercite is its patent quality metric AmberScore. This is a simple figure based on patent data which can predict the commercial importance of an invention.

Being from Australia, Ambercite was naturally interested in who the best Australian innovators were. AmberScore allowed us to answer this question by identifying the leading Australian patents. 

For this reason  AmberScope is proud to launch its report “Turning mousetraps into millions: Australia’s top ten patents and their role in Australian innovation”

In this report, we identify and rank the top 10 patents to come out of Australia, and discuss the organisations behind them.

Who will be on this list? CSIRO? Cochlear? Maybe little known entrapreneuers who have created world class products?

And for what products? WiFi? Polymer banknotes? Or maybe innovations that are all around us but we did not realise the role that Australian innovators had on their development?



We invite you to download the report by clicking on the image below, and then explore the world of Australia’s leading patents for yourself. And if you have any questions about the report or how we put it together, we would very happy to talk to you about these.



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Rapid and low cost patent due diligence – case study on advanced battery company Aquion Energy

One of the tasks that patent managers get called upon to do from time to time is patent due diligence during the buying or selling of companies. In theory a good due diligence assessment should include a patent attorney review of the every patent of the company concerned. Unfortunately in practice there is rarely the budget to do this, meaning that due diligence assessment is often limited to:

  • A simple legal check, namely that the patent details such as numbers are correct. While undoubtedly important, this is only part of the picture
  • A superficial review of some of the leading patents
  • A warranty provided by the vendor that they know of no IP issues. While these warranties are most likely provided in good faith, just because an IP risk is not know about does not mean that it does not exist.

I think we would all agree that a more comprehensive assessment is a good thing, but few of us have unlimited budgets. Ideally, this review would cover the following areas:

  • Patentability
  • Freedom to operate
  • Licensing Potential
  • Most important patents in the portfolio

Ambercite has recently released the new patent searching product “Cluster Searching“. Prior to its commercial release, it was tested extensively in commercial applications, including a number of due diligence applications. Pleasingly, it was found to be well suited as the following case study will show.


Case Study – Aquion Energy

Aquion Energy was founded in 2008 by Professor Jay Whitcare from Carnegie Mellon University, and claimed to have attracted venture capital funding from Kleiner Perkins, Bill Gates and Advanced Technology Ventures. Its technology is based on using saltwater as an electrolyte, claiming these batteries to be safe, room temperature, long cycle and low maintenance, making them very suitable for storage for wind and solar power. Products to date are based on ~ 2 kWh modules that can be easily stacked for high storage requirements.

From a patent point of view, Aquion has a limited number of patents and patent applications. This makes them ideal for a demonstration of the power of Cluster Searching.  

Cluster Searching is very easy to use – all you need is a suitable set of starting patents. We identified the following patents and patent applications as belonging to Aquion Energy, and entered them into Cluster Searching as our seed patents:


You will note that the above includes a date filter. This is very useful, as it can be used to set up different searches.

For due diligence, these searches could be for one or more of the following purposes:

  • Patent validity
  • Freedom to operate
  • Licensing potential.
  • Overall patent quality

These objectives will be considered separately.


Patent validity

For patent validity, we might run a ‘before’ search, i.e. all patents filed before a nominated date. The earliest priority date I could find for the patents is March 2011, so we might set a “before date” of March 2011



Running such a search, the five most similar patents to above starting patents are shown in the list below:


This suggests that some of the most similar patents are filed by FMC Corp and Valence Technology Inc. In fact there were a total of 22 patents (out of the most similar 1000) filed by FMC Corporation and 75 by Valence Corporation.

BTW, the interactive version of this table includes the ability to sort, filter, edit, copy and download these results. Each of the little blue circles in the image above will open up more details of the patent concerned. This is very helpful as it can be impractical to review one thousand patents individually – but it is practical to review say the top 20 to 50 patents in some details and then skim through the rest looking for relevant concepts in the patent title. 

From such a review, you should be able to form a preliminary view of the validity (with respect to the prior art) of the Aquion patents.


Freedom to operate

Freedom to operate requires an understanding of similar patents filed both before and after the priority date of the patents in question, or in other words all patents filed before the current date.



Because the priority date of these patents is quite recent, a very similar set of results is shown to the above query.



A patent analyst would from these results: 

  • Review the top ranked patents to see if Aquion was infringing any of these patents. 
  • Work out who the leading patent owners are, and ideally check to see if they did have any other patents that Aquion needed to be concerned about. For example, the first and third ranked patents are filed by FMC Corporation. FMC describes itself as ‘a diversified chemical company serving agricultural, industrial and consumer markets globally’, and one of their divisions is concerned with energy storage.  Similary Valence Technology describes itself as ‘the global leader in the development and manufacture of safe, long-life lithium iron magnesium batteries’. 


Licensing Potential

Does Aquion have the potential to license their patents to other companies? One way of asking this question is to look for similar patents filed after the priority date, ie the opposite to a prior art search. 



Not surprisingly, this will provide a different set of results:



It is also worth asking – what makes an ideal licensing candidate?

We suggest a combination of the following:

  1.  A high degree of similarity to the seed patent(s)
  2. A high commercial importance for the patent concerned. We predict commercial importance using our ‘AmberScore’ value, which is based upon the citation networks of a patent. Any score above 1.0 is better than average.
  3. The current ownership of the forward citation patent. Ideally we suggest that these be owned by companies who have commercialised the technology – particularly the technology claimed by your patents




If a company has more than one patent in this listing, the Licensing Potential values of these companies can be added together, to work out the company that might be interesting. If we do this, we see the following results:


This suggest that the company Polyplus Battery has the greatest total Licensing Potential, and hence should be investigated further to see if they might want or need a license. Polyplus Battery describes itself as  having:

made a major breakthrough in the development of protected lithium metal electrodes that enable the development of batteries with unprecedented energy density. …focused on the development of rechargeable and non-rechargeable Lithium-Air, Lithium-Seawater and Lithium-Sulfur batteries.


What are the best patents in the Aquion portfolio?

As a final analysis, we can rank the individual patents in the portfolio using the AmberScore metric. During the process of running any searches, the seed patents are listed in a separate table, and AmberScore values provided. This table can be sorted by AmberScore, and this can be used to show what may be the most important patents


This list shows that the two most important patents in the Aquion Energy portfolio may be US8652672 and US8298701. The first of these patents has a high number of backward citations and many indirect citations, showing a technical area with a lot going on – and this can be a predictor of patent value. The second patent also has a lot of backward citations, some forward citations, and again many relevant indirect citations.



There are other ways of performing this due diligence – but we doubt that any will provide as much information in a short a time as the analyses above.  Simply by inputting the patent numbers for the portfolio, we could make an intelligent assessment of the

  • Patentability
  • Freedom to operate
  • Licensing Potential
  • Most important patents in the portfolio

For this reason Cluster Searching has already been extensively used in commercial due diligence projects even prior to its public release. 


Interested in trialling Cluster Searching for yourself?

Ambercite offers a demonstration followed by a two week free trial – please contact us for further details.


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How to do a patent landscape search in as little at 10 seconds – a case study on Nest Labs

Nest Labs are a great example of a company that is helping to develop the ‘internet of things’. Founded by two former Apple engineers in 2010, the company was attracting major venture capital funding within months. Google Ventures invested in the company in 2011, with parent company Google buying out the whole company for $3.2 billion in January 2014. 

Nest have to date developed two types of products, being a home thermostat and fire alarm. Both are interesting choices in that home thermostats and fire alarms have both been around decades, and are commonly available at very low price points. However in both cases Nest have added value by incorporating smart features often based on internet access and control, and also through producing some of the most attractive home appliances I have personally seen for many years.

Looks aside, Nest Labs are an ideal candidate to demostrate our new cluster searching capability out. Cluster searching is a new option offered by Ambercite where the most similar patents to a cluster of ‘seed’ patents can be easily identified by the direct and indirect citation network around these patents.



While Ambercite has long been a proponent of citation searching from single patents using our AmberScope graphical patent search website, searching from a cluster of related patents has the potential to be even better. The reason for this is that, while individual examiners and applicants may miss or ignore relevant patents due to human error, personal preferences or the natural limitations of searching by keywords or classification codes, relevant patents are much less likely to be missed when searching from a cluster of patents.

If we take a cluster of seed patents, in most cases each patent would have had a separate patent search producing a separate list of patent citations. In addition each of the patents connected to these seed patents by direct patent citations would have had a separate patent search, agan producing a separate list of citations. The Ambercite Cluster Searching algorithms combine and focus what can be hundreds or even thousands of  these separate search reports so that the underlying patterns come out.  Faced with this deluge of patent citation linkages, relevant patents have a high chance of being found – they can have few places to hide.

This concept is very similar to the concept of the ‘Wisdom of the Crowds” – while an individual may not know the answer to every question, somebody in a crowd probably will. In our case, the ‘crowd’ is the all of the examiners and patent applicants that contributed their search reports to the patent citation network.


But enough of the concepts. What did we find?


What is a Nest Lab patent? How can we find them?

This is one of these simple questions that can be deceptively difficult to answer. We started by searching on the USPTO patent search website for patents and patent applications that were owned by ‘Nest Labs’, or patents that were assigned to or even from Nest Labs. Some of these patents have been subsequently assigned to parent company Google, but we included these as well. We then put all of these known patent numbers into our cluster search process –  and found more patents owned by Nest Labs, being, surprise surprise, some of the most similar patents to our known list of Nest patents.

We put these additional patents into our expanded list of Nest patents, and repeated the cluster analysis based on this expanded list of Nest patents (since each cluster search takes about 10 seconds to process, this is easy to repeat).



Looking at the patents we found, a number of them were filed by a Lawrence Kates, such as US7218237. Investigating these patents, we found via the USPTO Assignment search that these were also Nest patents (Nest being the second last owner before being assigned to Google).

We repeated the cluster searching iteration one more time with these Lawrence Kates patents, until finally we were comfortable that none of the patents that we found in our cluster search also belonged to Nest Labs.

This is more than a dry technical discussion about the nature of patent searching. A number of organisations are currently trying to improve the reliability of patent ownership data, and rightly so. This process suggests a method of checking the known patents owned by a nominated owner by running a cluster search, and reviewing the most similar patents to see if they are also owned directly or indirectly by the patent owner of interest..

Of course, this search will be complicated by the fact that there are two main Nest Labs technologies being thermostats and fire alarms. In some situations an analyst would separate out these two groups of patents before running a search. In other situations, for example an overall due diligence, the patents might be combined to build an overall picture of the landscape for the company itself.  This is what we have done in this case, particularly there is some cross-over in these technologies, such as presence detection and networking capability.


How many Nest patents did we find? How good are they?

Altogether we identified 181 patents using this approach , which an filing date range from 2004 to 2014, Figure 1. Note that this includes patents filed by Nest, acquired by Nest, or even assigned to Google (the owner of Nest) 


Ambercite believes that all patents are not equal, and has developed a metric to identify the more likely to important patents, based on their patent citations. In doing so we eschew a number of other value predicting factors used by some other analyts, such as family size (we have seen a number of very valuable US patents with small families, such as the $1.54 billion Carnegie Mellon patent).

This metric is known as AmberScore, and has been normalised so that the average granted US patent has an AmberScore of 1. Higher values suggest more important patents.

When we look at the Nest Labs patents, we see that a good proportion (38%) had AmberScore value greater than 1, Figure 2. This compares well with the ~26% for patents owned by Google and Apple, and 11% for patents owned by Microsoft seen in a recent comparison



What was the top ranked Nest patent?

This was US7047092, filed in 2004 for a Home automation contextual user interface. This claims:

1. A control unit for a home automation system comprising:

  • computing resources configured to execute application code on the control unit;
  • context information stored in the control unit;
  • a display presenting a graphical user interface;
  • a plurality of interactive user interface elements presented on the graphical user interface such that a single user interface element can simultaneously display information about the context as well as implement behavior to send messages to a controlled system that can affect change in the displayed information;
  • wherein the context information comprises state information known to the control unit, which includes context-specific state information known to a particular control unit as well as global context information known to multiple or all control units in a system



This patent had an AmberScore value of 10.7, which is very good.

Does this claim or protect the current Nest thermostat? Ambercite are not patent attorneys, but the Nest thermostat certainly appears to include a ‘context related interface’ to me.


What was the most similar patent not filed by Nest?

Ambercite cluster reports include a ranking of the overall similarity of the patents we found to the cluster of patents being searched upon (being the Nest patent portfolio in this case). Using this process, the most similar patent we found that was not filed by Nest was US8180492, filed by Ecofactor in 2009 for a System and method for using a networked electronic device as an occupancy sensor for an energy management system. Unlike Nest, Ecofactor offer only services to energy companies and other intermediates, but the relevance of the above patent to Nest Thermostat seems pretty clear to me.



What is the technology landscape around the Nest patents?

Some of the most common questions that people ask in these sorts of landscape surveys are:

• What are the leading patents?
• Who are the leading patent owners?
• Who could Nest Labs most likely license their patents to?

These questions become straightforward once we start employing the Ambercite metric AmberScore, which can be combined with similarity values to create the metric “Licensing Potential”

There Ambercite cluster searching can potentially allow the identification of many thousands of similar patents, ranked by predicted similarity. For the sake of simplicity in this blog, we have instead merely identified the 500 most similar patents that are filed after the year 2004, i.e. within the last 10 years. These patents are most likely to represent the latest developments in this now fast changing field. We will refer to these patents as the ‘Similar 500’ group of patents (please note that there are many other ways we could nominate patents for a patent landscape, such as the most similar 1000 patents, 5000 patents, patents filed in the last 20 years, etc).


Are these patents we found directly or indirectly connected to the Nest patents?

Of these 500 patents, 197 are direct citations to or from Nest patents, but 303 are not. But just because a found patent is not directly connected to a Nest patent it does not mean that it is not relevant. For  example, the most similar non-Nest patent we found that was not directly connected to a Nest patent was US8340826, filed in 2011 for a System and method for optimizing use of plug-in air conditioners and portable heaters. This claims control of a plug in cooler or heater that can be controlled by a remote computer, which is similar to the concept of hardwired heaters or coolers remotely controlled by a remote network.


What are the leading non-Nest patents?

Out of the Similar 500, the highest rated patents are by AmberScore are:



Patent title

Directly connected to Nest patents?

AmberScore (links to same patent in AmberScope)

US8694164  (filed 2009)

Lennox Industries

Interactive user guidance interface for a heating, ventilation and air conditioning system



US8744629 (2009)

Lennox Industries

System and method of use for a user interface dashboard of a heating, ventilation and air conditioning network



US7343226 (2006)

Invensys Systems (now Schneider Electric)

System and method of controlling an HVAC system




Who are the leading patent owners?

Since each patent has an AmberScore, it is also possible to work out the leading patent owners based on the total AmberScore value of their patents in the ‘Similar 500’ list:


Total AmberScore value in ‘500’ patent list

# of patents in ‘500’ patent list

Highest scoring patent

Most similar patent to Nest Labs list




US8066508, Adaptive spark ignition and flame sensing signal generation system, AmberScore value 7.8

US7801646, Controller with programmable service event display mode, AmberScore value 3.5




US7908117, System and method for using a network of thermostats as tool to verify peak demand reduction, AmberScore value 13.4

US8180492, System and method for using a networked electronic device as an occupancy sensor for an energy management system, AmberScore value 11.0




US8694164, Interactive user guidance interface for a heating, ventilation and air conditioning system, AmberScore value 25.5

US8744629, System and method of use for a user interface dashboard of a heating, ventilation and air conditioning network, AmberScore value 23.6


Who might Nest Labs most likely license their patents to?

Because we can calculate both how similar and important a forward citation patent, we can calculate the ‘Licensing Potential’ for any connected patents. The advantage of doing so is that this metric is additive, i.e. if an linked owner has more than one forward citation patent, these Licensing Potential values can be added.

The three patent owners with the greatest predicted licencing potential echo the top three companies previous mentioned


Total Licensing potential in Similar 500’ patent list

# of patents in ‘500’ patent list

Patent (and therefore patented invention) with highest Licensing Potential from Nest portfolio




US8167216, User setup for an HVAC remote control unit, Total Licensing Potential 28.4




US8180492, System and method for using a networked electronic device as an occupancy sensor for an energy management system, Total Licensing Potential 50.7




US8694164, Interactive user guidance interface for a heating, ventilation and air conditioning system, total licensing potential 47.0.


It should be noted that none of this implies in any way that any of Honeywell, Ecofactor or Lennox will need a license from each other, as a lot of other investigative work will be required before anybody knows this.  But it is to say that patent attorneys looking for licensing opportunities in this area might start with some of the patents and patent owners referred to this blog, even if the they looked at these patents on a one by one rather than cluster searching basis.


How else do people run patent landscape searches? How do these other methods compare?

There of course many ways that people can do patent landscape searches to find similar patents to a known portfolio. The most common means include more traditional keyword and class code searches. And there are perfectly fine, as long as you accept the limitations of these other techniques:

  • Not all patents found in a keyword and/or class code patent landscape search are going to be relevant. The same applies to an Ambercite cluster search, but we pretty happy with the overall degree of relevance for cluster searches.
  • Similarily we can almost guarantee that no matter how carefully a keyword search is put together, there will be relevant patents that use different keywords. But the beauty of cluster searching is that becauses it compiles the citations opinions of many different examiners and applicants, you are more likely to find relevant patents even with very different technical terms (or even find patents published in different language)
  • It will take time to develop the queries, run the search, fine tune the query. In contrast a cluster search only requires knowledge of the patents in the portfolio, and does not require any other assumptions or specialist knowledge. Instead it is the patents themselves that drive the patent search. The results are delivered in seconds, making it ideal as a preliminary screening tool when time and budget is limited.


When compared to more conventional forms of patent searching and landscaping, this can be described like driving an automatic transmission car compared to a manual transmission car. Yes, there are many people who prefer to drive a manual car and who appreciate the added control that comes from this. But in many countries the vast majority of cars now sold are in automatic form. Increasingly premium and even sporting cars are being sold without an manual option. Drivers and car manufacturers both realise that an automatic transmission can be smarter than even the best of manual drivers –  and in any case most drivers prefer to have something else do the thinking for them.




Using Cluster Searching is like driving an automatic – you don’t need to think about the right keywords or classifications or other search strategies – instead you simply need to input a known list of suitable seed patents, and within seconds you will have a list of similar patents. It really is that simple.

Further information about Cluster Analysis

Cluster analysis is now being used by patent owners worldwide for invalidity, licensee and FTO searching and will soon be available in online and API (Application Programming Interface) and bulk ‘smart data’ form. Please contact us if you are interested in further information.

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