Provides overview of Issues

1. 1
Protecting Emerging Technologies in the World of Internet of Things (IoTs), Artificial
Intelligence (AI), Wearables, and Graphical User Interfaces (GUI)s: Protecting, Defending
and Monetizing an Internet of Things (IoT) Patent Portfolio
Dennis J. Duncan¥
I. Introduction
Integrating emerging technologies into a business’s existing product line or suite of
services has always been a challenge for intellectual property (IP) counsel trying to secure
adequate IP protection as well as to monetize new products that exploit the integrated new
technologies. Typical challenges in providing adequate IP protection include the fact that many
new innovations merely automate well-known processes or apply a known technique to a known
device, thereby making it difficult to secure patent rights.1
Another related challenge is keeping
track of engineers who might seek shortcuts in the new automating technology by including
computer software into existing products or services which may have open source issues and
which could obliterate a business’s existing patent portfolio. Another more basic challenge
might be the lack of understanding of the patent landscape of the emerging technology as it
relates to the business’s existing product line or suite of services. That is, if the landscape is
unknown, IP counsel might file the patent application too early (before their innovators fully
developed the final product or service), or too late, thereby allowing a competitor to beat the
business to the patent office. Or, in the case of a design patent application directed to a graphical
user interface (GUI), filing too early might require the filing a second, costly application if
significant changes are made to the design of the interface. Once the trigger is pulled and the
emerging technology is implemented into the business’s existing product line or suite of
services; added unforeseen costs from the assertion of patents by holders of the emerging
technology might significantly affect the profit margins of the emerging technology.
¥
Dennis J. Duncan is a Senior Patent Counsel at Dolby Laboratories where he manages a global patent portfolio. The views
expressed herein are his own and not necessarily those of Dolby Laboratories. Moreover, the opinions expressed herein are not
to be considered legal advice. Anyone considering filing a patent application should retain competent counsel in the relevant
jurisdictions to avoid loss of patent rights and to avoid possible civil and criminal penalties.
1
See MPEP 2100 under Subsection C. (Use of Known Technique To Improve Similar Devices (Methods, or Products) in the
Same Way) and Section D. (Applying a Known Technique to a Known Device (Method, or Product) Ready for Improvement To
Yield Predictable Results). See also In re Nilssen, 851 F.2d 1401, 7 USPQ2d 1500 (Fed. Cir. 1988) (employing well-known
circuit protection cutoff switch to provide desired protection in a well-known inverter circuit); Dann v. Johnston, 425 US 219
(1976) (employing automated machine system for automatic record-keeping of bank checks and deposits).

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Currently, IP counsel now face an amalgamation of integrated emerging technologies by
way of the so-called internet of things (IoTs). IoT is a technology concept which covers a web
of connected devices typically controlled over a wireless data network. That is, many different
possibly emerging technologies which come together create an IoT system. The fact that IoT is
predominately wireless presents additional challenges for IP counsel in certain business sectors
besides the one listed above. The additional challenges come about because IoT’s wireless
component includes radio frequency (RF) radiation which requires compliance with various
governmental and industrial standards and/or certifications. The most challenging industry for
these concerns points to an IoT which senses (or renders on or near) a human being (i.e.,
wearable smart devices).
Further, proving infringement, as well as monetarizing product lines or suites of services
which are deployed as part of an IoT creates even more challenges with respect to a larger
number of potential licensors. Just the 3G and 4G patent holders alone could scare off existing
businesses from becoming part of an IoT invention as the profit margins will surely decrease.
II. Internet of Things (IoTs)
The Internet of things (IoTs) is often described by way of a technological concept or a
framework or system, including a web or an array of connected devices which may be
configured as sensors, actuators or display/renders that are in communication and are controlled
over a data network.2
Such data networks are typically interconnected, predominately by way of
wireless links which may include various well-known wireless standards (e.g., 802.11xx) and
legacy cellular networks (e.g., GPRS, EDGE, WCDMA, HSPA/ HSPA+, 1xRTT and EV-DO)
and advanced cellular networks (e.g., LTE/LTEA/LTEA Pro, 5G), as well as short-range RF low
latency person area networks (PANs) (e.g., Bluetooth, ZigBee, Wireless Hart and RFID) and
very low latency PANs (e.g., Sigfox, RPMA, LoRa, LTE-M and LTE-NB).3
That is, many
different technologies and interconnected devices can come together to create an IoT system.
2
For a medium-level technical overview of a wireless Internet of Things System, see Lee Vishloff, "Wireless for the Internet of
Things (IoT), IEEE COMSOC Training Course November 8, 2017.
3
Id. See also. “Internet of Things: Wireless Sensor Networks,” White Paper, IEC 2014.

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Others define IoT as an ecosystem representing:
A global network and service infrastructure of variable density and
connectivity with self-configuring capabilities based on standard and
interoperable protocols and formats [which] consists of heterogeneous things
that have identities, physical and virtual attributes, and are seamlessly and
securely integrated into the Internet.4
Various standards organizations such as International Telecommunication Union (ITU),5
World Wide Web Consortium (W3C),6
Internet Engineering Task Force (IETF),7
Institute of
Electrical and Electronics Engineers (IEEE)8
as well as various industrial initiatives such as the
Allseen Alliance/ Open Connectivity Foundation,9
the Industrial Internet Consortium,10
the
Platform Industrie 4.011
and the Thread Group12
have been investigating collaboration on IoT
and/or have adopted standards (or are in the process of adopting standards). One prominent IoT
standard is ETSI’s machine2machine (M2M) IoT standard which is described as encompassing
‘everyday machines and objects embedded with sensors or actuators and [that] have the ability to
communicate over the Internet’ having potential applications and services such as: smart devices,
smart cities, smart grids, the connected car, eHealth, home automation and energy management
and remote industrial process control.13
4
Andreev, Sergey, et. al. (Eds.) Internet of Things, Smart Spaces, and Next Generation Networking, 12th
International Conference, NEW2AN 2012, and 5th Conference, ruSMART 2012, St. Petersburg, Russia, August 27-
29, 2012, Proceedings (citing Tarkoma, S. Katasonow, A.: Internet of Things Strategic Research Agenda. Finnish
Strategic Centre for Science).
5 Global Standards Initiative on Internet of Things (IoT-GSI).
6
Web of Things (WoT) ( ”. . . seeks to counter the fragmentation of the IoT through standard complementing building blocks
(e.g., metadata and APIs) that enable easy integration across IoT platforms and application domains. “)
7
According to IETF, “Several working groups, spanning multiple areas within the IETF are developing protocols
that are directly relevant to the IoT. In many cases, there is little or no organized coordination between these
working groups.”
8
2413 - Standard for an Architectural Framework for the Internet of Things (IoT) (draft) 5/2017.
9
See. http://www.eweek.com/networking/iot-standards-groups-ocf-allseen-alliance-merge (Visited October 12,
2017) (“AllSeen Alliance, one of the early industry consortiums aimed at creating open interoperability standards
for the internet of things, is being absorbed by another group with similar ambitions, the Open Connectivity
Foundation.”) See https://www.ge.com/digital/blog/everything-you-need-know-about-industrial-internet-things
(Visited November 23, 2017).
10
Consortium formed by AT&T, Cisco, General Electric, IBM, and Intel to accelerate the development, adoption
and widespread use of interconnected machines and devices and intelligent analytics.”
11
A German-based consortium with over 250 participants from more than 100 organizations.
12
Founded by google (Alphabet), Samsung Electronics, Arm Holdings, Freescale Semiconductor (now part of NXP
Semiconductors) and others seeking to create an open wireless protocol designed to connect hundreds of low-power devices to
one other and to the cloud.
13
http://www.beechamresearch.com/download.aspx?id=18 (Visited November 2, 2017).

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III. RF Transceivers: Compliance with Part 15 Regulations and Carrier Certifications and
Trademarks
Many of the various component endpoints of an IoT system as described require compliance
with various Federal Communication Commission (FCC) regulations (e.g., Part 15
Requirements)14
and in some circumstances certification by a cellular carrier’s connectivity
standards.15
Further, some wireless standards such as Bluetooth,16
WiFi,17
LTE18
and Zigbee19
might require obtaining permission to use various trademarks on a product or service as well as
advertising material.
IV. Design Patents Graphical User Interfaces (GUIs)
Many end points in an IoT system might employ a graphical user interface (GUI) which
might require consideration of filing a design patent in addition to a utility application to cover
the so-called ‘look and feel’ of the invention. That is, due to cost constraints, an omnibus IoT
utility patent application might be filed detailing the functionality of a GUI, together with the
14
https://www.fcc.gov/oet/ea/rfdevice (Visited November 2, 2017)
15
“Compliance Design & Certification for IoT Cellular Applications,” DIGI 2017
(https://www.digi.com/pdf/iot_design_certs_cellularapps.pdf (Visited November 20, 2017))
16
https://www.bluetooth.com/develop-with-bluetooth/marketing-branding/brand-guide-logos (Visited November 12, 2017) (The
Bluetooth Special Interest Group (SIG) owns Bluetooth trademarks. “In order for a company to use the trademarks, two things
must happen: 1) a company must be a member of the Bluetooth SIG and 2) the goods offered must be fully qualified and declared
through the Bluetooth Qualification Process.”).
17
Use of the Wi-Fi Certified logo and our other certification marks is limited to Wi-Fi Alliance members only.
18
See. “Guidance for use of the LTE logo” (Anyone wishing to use the LTE logo must e-mail the following information: (1)
Company Name and address & website URL, (2) Your details : First name, Family name & position within the company, (3)
Reasons for requesting the use of the LTE trademark and/or LTE, LTE-Advanced and/or LTE-Advanced Pro logo, (4) The nature
of the intended use of the LTE trademark and/or the LTE, LTE-Advanced and/or LTE-Advanced Pro logo, (5) Countries you
would expect to use the LTE trademark and/or the LTE, LTE-Advanced and/or LTE-Advanced Pro logo, and (6) 3GPP
Organizational Partner your company is a member of, if appropriate.”).
19
ZigBee Designations and Logos Policy, ZigBee Alliance, November 16, 2012 (To use the ZigBee certified Logo a device
must: “1. Be products with Stock Keeping Unit (SKU) code and/or Universal Product Code. 2. Be designed with an unchanged
ZigBee Compliant Platform. If any part of the ZigBee Compliant Platform has changed, the product must be recertified. 3. Be
based on an interoperable ZigBee Alliance standard (public application profile). 4. Have successfully completed the applicable
ZigBee Certified product test program through a test service provider approved by the ZigBee Alliance. 5. Have submitted all
documentation required. 6. Have received a certification letter from the ZigBee Alliance.”)

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utility application. In such scenarios, the applicant should be careful to avoid statements in
utility patents that could negatively impact the validity of related GUI design patent applications.
To avoid such a scenario, counsel should avoid disclosing the GUI in a figure in the specification
and also avoid stating that a GUI has a particular form (if this is not the case). If counsel is
required to add the GUI as a figure, they should include one or more statements that the GUI
depicted is merely provided as an example embodiment and need not take that particular form
shown in the utility patent drawings figures to achieve whatever stated function is described in
the specification. See PHG Techs., LLC v. St. John Companies, Inc., 469 F.3d 1361, 1364 (Fed.
Cir. 2006) (invalidity of two design patents raised on the basis that the patented designs were
merely a byproduct of functional considerations); Ethicon Endo-Surgery, Inc. v. Covidien, Inc.,
796 F.3d 1312, 1330 (Fed. Cir. 2015) (among other things, raised several issues of whether
protected design represents the best design as well as whether alternative designs would
adversely affect the utility of the specified article).
V. Artificial Intelligence (AI)
The glue (or rather the backend) of IoT interconnectivity and efficiency are application
programming interfaces (APIs) employing machine learning or deep learning algorithms,
together with big data analytics to optimize the communication of data and coordination of
communication in an IoT system by way of supervised (e.g., classification) or unsupervised (e.g.,
pattern analysis) learning. Machine learning and deep learning are a sub-branch of artificial
intelligence. Patent applications directed to AI subject matter need to carefully consider Sections
101 and 112, as well as possible open source issues as discussed below.
A. AI Subject Matter Patentability Issues
Patent applications directed to AI subject matter have unique patentability issues with respect
to Sections 101 and 112. That said, a recent study by Oracle found that roughly 87.5% patents

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directed to AI subject matter received allowances in the USPTO.20
However, looking more
closely at those issued patents reveals that the patent claims are narrowly focused on the relevant
AI technical details, such as the machine learning or deep learning aspects. That said, patent
counsel should carefully consider whether obtaining a patent directed to AI technology with
narrow claims is worth the effort unless the patent is used in a product or service. If not used in a
product or service, one might obtain a seemingly non-nonsensical patent that might end up
appearing on the Electronic Frontier Foundation’s stupid patent of the month list.21
1. 35 U.S.C. §101 Subject Matter Eligibility (“effect of steps of the algorithm”)
The invention must be directed to a patent-eligible concept and not a law of nature,
natural phenomenon or an abstract idea.22
If directed to an abstract idea, the claims must be
directed to something significantly more and must include an inventive concept.23
For an AI
subject matter invention, the claims must be crafted to improve the performance of a computer
system. Moreover, the claims typically need to include specific limitations which are application
of AI technology and described as an improve in the technology and not to the effect of the
technology or results. The claims should also be drafted in such a manner as to avoid the
perception that the applicant is attempting to preempt the specific field of technology (i.e., too
broad”). One such example is U.S. Patent No. 9,563,840: “System and Method for Parallelizing
Convolutional Neural Networks”.
During prosecution of U.S. Patent No. 9,563,840, the Examiner found that the
Applicant’s claimed invention was directed to non-statutory subject matter under Section 101
(see March 7, 2016 Non-Final Office Action Application Serial No. 14/817,492). That is, the
Examiner determined that independent claim 2 recited a “convolutional neural network system”
comprising: a sequence of neural network layers” which generate “a sequence output for the
input image.” Similarly, the Examiner found that independent claim 12 recited a “method for
20
See Eric Sutton, “Artificial Intelligence: Data Driven Guidance for Patent Portfolio Management,” 2017 IPO Annual Meeting,
September 18, 2017 (review of patent applications filed after 2011 in Art Unit 2100).
21
See https://www.eff.org/deeplinks/2017/09/stupid-patent-month-will-patents-slow-artificial-intelligence (visited November 29,
2017) (Article where the Electronic Frontier Foundation criticizes the US Patent Office’s on the ground that it “. . .reviews
applications without ever looking at real world software and hands out broad, vague, or obvious patents on software concepts.”)
22
35 U.S.C. § 101
23
Alice Corp. v. CLS Bank International, 134 S. Ct. 2347 (2014)

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processing an input image using a convolutional neural network system comprising a sequence
of neural network layers” which generates “a sequence output for the input image.” In sum, the
Examiner determine that both claims 2 and 12 where directed to abstract mathematical
operations and mathematical results which can be obtained by mental and hand calculation for an
appropriately sized model and input “image”). Claim 21, which was presented in classic
Beauregard format, was similarly rejected under Section 101. In a subsequent Examiner
interview, the Examiner further clarified that ‘a sequence output for the input image’ generated
by a convolutional neural network” was merely an abstract idea (i.e., mathematical operations
and results) “because such an output, once generated and not displayed or practically used, is
simply an effect of steps of the algorithm used to implement the convolutional neural network
starting from receipt of an ‘input from an input image”. (See May 13, 2016 Examiner Interview,
Application Serial No. 14/817,492).
To overcome the Section 101 rejection, the Applicant amended independent claims 2 and
12 to indicate that the convolutional neural network is “implemented by one or more computers”
and “configured to receive an input image and to generate a classification for the input image”.
Id. Independent claim 21 was amended to recast the traditional Beauregard claim to multiple
processes indicative of a neural network (e.g., “one or more non-transitory computer readable
media encoded with a computer program” and to generate a classification for input image”).
2. 35 U.S.C. §112 enablement, written description and definiteness
a. 35 U.S.C. §112(a) Enablement (express, implicit or inherent support)
Another common problem in drafting claims directed to AI inventions is failing to
adequately describe the subject matter in the specification. Section 112 indicates that the
specification supporting claimed subject matter must describe in ‘full, clear, concise and
exact terms any algorithms or processes to enable any person skilled in the art to make and
use the invention without undue experimentation at the time the application was filed. 35
U.S.C. §112(a). Further, MPEP 2163 indicates that claimed subject matter must be

8. 8
“expressly, implicitly, or inherently supported in the originally filed disclosure.”24
Such
support could be a description or reference to a published scholarly journal article or
conference paper (incorporated by reference25
) which reasonably conveys to one skilled in
the art with reasonable certainty in view of what is disclosed and in view of the teachings
available to one skilled in the art at the time of the filing date.
b. 35 USC §112(b) Written Description (Gaps Between Steps MPEP §2172.01)
Another common problem with AI inventions is the tendency to omit essential steps. Such
omissions might amount to a gap between the steps.26
Similarly, care should be taken by the
drafter of the patent application to avoid omitting a step without which the invention as claimed
would be wholly inoperative (e.g., it simply would not work and could not produce the claimed
product). Also, the specification should provide several working or prophetic examples to avoid
possible 112(a)/112(b) rejections during prosecution.27
c. 35 U.S.C. § 112(f) Means-Plus: Modules, Units, Device, Network, Processor &
Code
With respect to inventive subject matter directed to Artificial Intelligence (AI), Machine
Learning (ML) and Deep Learning (DL), care needs to be taken when drafting the specification
in order to provide support for functional claims, and to avoid invoking 35 U.S.C. §112(f) when
claiming the structural elements of the AI framework. That is, improper functional claiming
can become a serious problem during prosecution. On the other hand, proper functional claiming
can allow the drafter to control to some extent the scope of the claims. Accordingly, if the AI
framework is claimed properly using functional language with structures clearly described in the
24
In re Robertson, 169 F.3d 743, 745, 49 USPQ2d 1949, 1950-51 (Fed. Cir. 1999) (“To establish inherency, the extrinsic
evidence ‘must make clear that the missing descriptive matter is necessarily present in the thing described in the reference, and
that it would be so recognized by persons of ordinary skill. Inherency, however, may not be established by probabilities or
possibilities. The mere fact that a certain thing may result from a given set of circumstances is not sufficient.’”).
25
Should the applicant seek protection outside the U.S., then the subject matter of the reference supporting the enablement should
be copied or paraphrased into the disclosure with proper citation to the reference.
26
In re Mayhew, 527 F.2d 1229, 188 USPQ 356 (CCPA 1976) (“claims failing to recite a necessary element of the invention fail
for lack of an enabling disclosure). See also MPEP § 2164.08(c). Such essential matter may include missing elements, steps or
necessary structural cooperative relationships of elements described by the applicant(s) as necessary to practice the invention.
However, the method claims omitted a step without which the invention as claimed was wholly inoperative (meaning it simply
would not work and could not produce the claimed product).
27
MPEP §2164.02. See also. In re Robin, 429 F.2d 452 (CCPA 1970)

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specification and during prosecution, the claimed invention can maintain some degree of
equivalents for elements amended for reasons of patentability.
Williamson and the District Court cases that have followed28
have provided some
guidance with respect to drafting patent applications directed to AI subject matter. For example,
Williamson v. Citrix Online, LLC, 792 F.3d 1339 (Fed. Cir. 2015) (en banc) as well as MPEP
2181 indicate that patent counsel should avoid ‘black box’ modules in the claims by way of
inserting generic placeholder (or so-called nonce terms29
) in the claims as a substitute for the
term “means” or “step.” That is, if counsel wishes to avoid invoking Section 112(f). In sum, in
drafting applications directed to AI subject matter, patent counsel should make sure that claims
for processors and circuitry are supported by sufficient descriptions of the algorithms that
perform the specialized claimed functions. The best practice would be to provide a description
in the disclosure along with one or more detailed flowcharts in the figures providing step-by-step
descriptions of the procedure.
An alternative to patenting the AI subject matter might be to maintain the invention as a
trade secret. However, a possible drawback would be that there would be no protections against
a competitor reverse engineering the AI invention, and no protections against a competitor
independently creating the AI subject matter.
VI. Open Source Issues:
Deep Learning (DNN) algorithms typically rely upon various code libraries and
repositories which may be subject to restrictive or permissive grants pursuant to an Open Source
Software license. For example, Lasagane appears to use an Apache licenses, TensorFlow
appears to use an MIT License, Torch appears to use a BSD License, while Caffe might use a
28
For an excellent review of recent District Court cases post – Williamson, see Doris J. Hines and Theresa Stadheim, “Functional
Claiming for Mechanical and Electrical Arts: Surviving 112(f) and Disclosing Functional Basis to Meet Heightened Standard of
Review,” Strafford Webinar, September 7, 2017.
29
The following nonce words have been listed as invoking Paragraph 6: “mechanism for,” “module for,” “device for,” “unit for,”
“component for,” “element for,” “member for,” “apparatus for,” “machine for,” and “system for.” The following terms have
been held not to invoke Paragraph 6: “circuit for,” “detection mechanism,” “digital detector for,” “reciprocating member,”
“connector assembly,” “perforation,” “sealing connected joints,” and eyeglasses hanger member.” See also Doris J. Hines and
Theresa Stadheim, “Functional Claiming for Mechanical and Electrical Arts: Surviving 112(f) and Disclosing Functional Basis to
Meet Heightened Standard of Review,” Strafford Webinar, September 7, 2017, pp 12-13.

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BSD2-Clause licenses. Making matters even more challenging is the fact that some DNN
software libraries such as Turi include a license attribution list which includes numerous third-
party entities. Others, such as Theano, appear to have their own open source license. For small
corporations and solo inventors, the importance of avoiding distributions and the possibility of
being subject to a copy left provision in an OSS might be devastating to patent rights.30
Large
corporations typically have Open Source Boards which oversee training of the company’s
engineers and technicians. For example, some companies may implement OSS portals to
determine whether the research and development teams can use OSS or contribute to OSS.
VII. Divided Infringement of IoT systems
With respect to enforcement of IoT patents, recent Federal Circuit cases, as well as 35 U.S.C.
§271, need to be considered with respect to divided infringement.31
For example, Akamai
Techs, Inc. v. Limelight Networks, Inc., held that that a single entity may be responsible for
another’s performance of claimed steps if the entity “directs or controls” the other’s
performance, or the entity and the other constitute “a joint enterprise.” 797 F.3d 1020 (Fed. Cir.
2015) at 1022. In other words, the scope of the claims of an IoT patent might be directed to the
infringer who “controls the system and obtains benefit from it.” See Centillion Data Sys. LLC.
v. Qwest Communs. Int’l Inc., 631 F.3d 1279, 1285 (Fed. Cir. 2011) (holding that the end user
might directly infringe the system claim that covers both a “front-end” system under the control
of the subscriber and a “back-end” system controlled by an operator/service provider). A recent
Federal Circuit case suggests that Akamai’s two-prong test might “[i]n the future, other factual
scenarios may arise which warrant attributing others’ performance of method steps to a single
actor. Going forward, principles of attribution are to be considered in the context of the particular
facts presented.” Eli Lilly & Co. v. Teva Parenteral Medicines, Inc., Appeal No. 2015-2067 (Fed.
Cir. Jan. 12, 2017).
30
See. Heather J. Meeker, The Open Source Alternative: Understanding Risks and Leveraging
Opportunities, February 2008; Michael Atlass, “Contributing to or Staring an OS Project: What’s
in it for your client, and How can you help?” AIPLA Spring Meeting, May 2016.
31
James Stein and Kenie Ho, “3 Challenges For Internet-Of-Things Patents” LAW360, June 10, 2016.

11. 11
VIII. Monetization of IoT/SEP patents
Various governmental entities across the globe have been investigating how to monetize
standard essential patents (SEP) directed to IoT.32
For example, the European Commission on
Standards hosted several workshops entitled “Best Practices and a Code of Conduct for
Licensing Industry Standard Essential Patents in the Internet of Things (IoT) / Industrial
Internet” in October 2017.33
The workshop resulted in the development a European vision of
SEP licensing that supposedly strikes the optimum balance between the rights and interests of
various stakeholders taking part in the creation of 5G/IoT ecosystem.34
The Japanese Patent
Office’s new Commissioner, Naoko Munakata, has continued Japan’s lead in creating an IP
System for the IoT Era (so-called IP 4.0) which seeks to characterize SEPs as an ‘infrastructure
for IoTs.35
Furthermore, several IoT/SEP holders, such as Ericsson, InterDigital, KPN, Qualcomm,
Sony and ZTE, have come together to form a ‘platform’ called “Avanci”36
that shares many of
the characteristics of a patent pool and is directed to a new scheme to monetize 2G, 3G, and 4G
technologies available to IoT device manufacturers who are adding connectivity to their
products.37
Just recently Avanci announced their first licensee, The BMW Group.38
32
Joff Wild, “European Commission DGs square up in crucial fight over SEP licensing guidelines,” October 26, 2017.
33
https://www.cencenelec.eu/news/workshops/Pages/WS-2017-011.aspx (Visited October 29, 2017)
34
European Commission, “Communication from the Commission to the European Parliament, The Council and The European
Economic and Social Committee: Setting out the EU approach to Standard Essential Patents,” November 11, 2017.
35
See “Intellectual Property 4.0”, Naoko Munakata, Commissioner Japan Patent Office, September 17, 2017 IPO
Annual Meeting.
36
http://avanci.com/ (Visited November 1, 2017)
37
Richard Lloyd, "E Pluribus Unum – the continuing evolution of patent pools," Intellectual Asset Management, May/June 2017
pp17-20 at 19
38
Avanci Announces Patent License Agreement,” Business Wire, December 1, 2017.

12. 12
IX. Conclusion
IoT as described above provides many challenging IP issues when integrated into a
business’s existing product line or suite of services with respect to securing adequate IP
protection, proving infringement and monetizing new products that exploit the IoT.