Tuesday, March 21, 2017
Monday, March 20, 2017
IoT (Internet of things) big data analytics is becoming important to process unimaginably large amounts of information and data that are obtained by the sensor embedded interconnected IoT devices. The typical IoT big data analytics system is Hadoop, an open-source software framework that supports data-intensive distributed applications, and the running of applications on large clusters of commodity hardware. Hadoop, that is based on the architectural framework MapReduce, collects both structured data and unstructured data, processes the collected data set in a distributed network cluster in parallel, and extracts valuable information from the processed data set within a short time.
IBM patent application US20160070816 illustrates a system for processing large scale unstructured data in real -time. The interconnected IoT sensing devices continuously generate massive information at a very high speed. Thus a technology for effectively processing a huge amount of information in the form of a data stream in real-time is very important. The real time big data analysis system includes a receiver for receiving streamed input data from live data sources, a pattern generator for deriving emergent patterns in data subsets, a pattern identifier for identifying a repeating pattern and corresponding data subset within the emergent patterns, a compressor for reducing the identified data subset and identified pattern to a compressed signature and a repository for storing the streamed input data with the compressed signature and without the identified data subset in which the data subset can be rebuilt if necessary using the compressed signature.
In IoT, millions of events often generated from IoT sensors and devices. Thus, it is very important to develop real-time data streaming and processing systems for IoT analytics. There are several open-source real-time data streaming and processing systems are available including Apache Kafka, Storm, and Spark. Most of open-source real-time data streaming and processing systems offer default schedulers that evenly distribute processing tasks between the available computation resources. However, such schedulers are not cost effective because substantial computation resources are lost during assignment and re-assignment of tasks to the correct sequence of computation resources in the stream processing system, which results in significant latency in the system. Salesforce.com, inc. patent application US20170075693 illustrates a cost effective improved real-time data streaming and processing systems for IoT analytics.
In Industrial IoT (IIoT) applications (e.g., manufacturing, oil and gas, mining, transportation, power and water, renewable energy, heath care, retail, smart buildings, smart cities, and connected vehicles), it is not practical to send all of that data from sensors embedded in industrial machines to cloud storage because connectivity not enough bandwidth in a cost effective way and difficulty in practical implementation of effective real-time decision making and prediction systems. FogHorn Systems, Inc. patent application US20170060574 illustrates a real-time edge IoT analytics system (e.g., Fog Computing) that can handle the large amounts of data generated by industrial machines and provides intelligent edge computing platform.
Data monetization is a business model to generate revenue from available data sources or real time streamed data by instituting the discovery, capture, storage, analysis, dissemination, and use of the data. Data monetization leverages data generated through business operations as well as data associated with individual actors and with electronic devices and sensors participating in a given network. IoT can facilitate generating location data and other data from sensors and mobile devices. Big data system enables identification, analysis, selection and capitalization of the IoT data monetization opportunities. Data monetization value chain includes the data producers, data aggregators, data distributors and data consumers. Data as a service (DaaS) models for transactions involving big data can be possible.
mFrontiers, LLC patent application US20160050279 illustrate a system for operating the IoT big data analysis service for data monetization. The system analyzes the stored data from the IoT devices in the cloud and produces a big data analysis report. A client can purchase or sell information on the analyzed big data analysis report through the virtual big data marketplace. The big data analysis report can include information on a preliminary analysis report whose results vary according to analysis time or period. When a third party analyzes big data using the information on preliminary analysis report, a writer who uploaded the information on preliminary analysis report to the analysis report marketplace charges fees for the information.
New Technologies & Associates, Inc. patent application US20150179079 illustrates a healthcare IoT big data analytics system for real time monitoring of a patient's cognitive response to a stimulus. The big data analysis of massive data obtained by the sensing devices can provide many value-added healthcare services. The real time monitoring system includes a mobile or tablet device, a user interface disposed on the mobile device, sensors monitoring user interaction with the mobile device and capturing kinesthetic and cognitive data. The real time monitoring system also includes a processor for comparing the kinesthetic and cognitive data and comparing the data to a baseline, and identifying relative improvement and impairment of cognition skills from the comparison exploiting big data analytics.
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Friday, March 17, 2017
By exploiting a big data patent search and analysis tool - the IPlytics Platform (Ref. https://www.slideshare.net/alexglee/iplytics-platform-introduction), TechIPm, LLC (www.techipm.com) extends its more than 6 years of custom research of LTE patents to include a large number of new candidates for the LTE standard essential patents (SEPs). The IPlytics Platform data sources cover over 80 million patent documents for 98 worldwide countries, over 60 million scientific articles, information regarding over 3 million companies, about 2 million standards documents from 96 standard setting organizations including over 200,000 SEPs declared at the major standard setting organizations (SSOs).
LTE issued patents for the LTE UE (cellular phones, smart phones, PDAs, mobile PCs, etc.), base station (eNB) products, and other RAN (Radio Access Network) related products are searched in the USPTO as of 1Q 2017. The searched patents are further reviewed with respect to 3GPP Release 10 technical specifications (LTE-Advanced) for LTE RAN technical specifications: PHY: TS 36.101, 211, 212, 213, 305; L2/L3 Protocols: TS 36.300, 304, 321, 322, 323, 331, 355 and 3GPP Release 11 technical specifications for CoMP (TR 36.819), 3GPP Release 12 technical specifications for EPDCCH (TS 36.211, 213) and D2D (Device to Device; TR 36.843) Communications.
The identified LTE standard related patents cover not only ETSI declared SEPs but also candidates for SEPs that were not declared. Nearly 4000 US issued patents are finally selected as the LTE standard related patents. The identified LTE standard related patents are also updated for the current assignees.
The identified LTE standard related patents are further categorize through the evaluation process by technologies for implementations of the LTE baseband modem ( OFDM/OFDMA (Frame & Slot Structure, Modulation), SC-FDMA (PUSCH, PUCCH), Channel Estimation (UL RS, DL RS, CQI), Cell Search & Connection (PRACH, DL SS), MIMO (Transmit Diversity, Spatial Multiplexing), Resource Management (Resource Allocation, Scheduling), Coding (Convolution, Turbo), Power Control, HARQ, Carrier Aggregation, Relay, and Positioning Technology) and radio protocols (Random Access, HARQ, Channel Prioritization, Scheduling (Dynamic, SPS), Protocol Format (PDUs, SDUs), Radio Link Control (ARQ), PDCP Process (SRB, DRB, ROHC), Security (Ciphering, Integrity), System Information, Connection Control, Mobility (Handover, Inter-RAT, Measurements), QoS, MBMS, and Carrier Aggregation). To evaluate the essentiality of a LTE patent, patent disclosures in claims and detail description for each LTE related patent also are compared to the LTE technical specifications.
Leaders in LTE standard related patents IPR ownership as of 1Q 2107 are Qualcomm followed by InterDigital, Samsung Electronics, LG Electronics, Google, Ericsson, Nokia (+ Alcatel-Lucent), Apple, Panasonic, Optis Wireless Technology LLC, Intel, Huawei, NTT Docomo, ZTE, BlackBerry, Amazon, NEC, Texas Instruments, and ETRI. Here, most of Amazon’s LTE patents were acquired from LG Electronics.
For more information, please contact Alex Lee at firstname.lastname@example.org .
Monday, March 13, 2017
how IoT could have the biggest impact on people, places and things.
Harel Kodesh, Vice President, Predix & CTO, GE Digital
Mac Devine, VP & CTO, Emerging Technology & Advanced Innovation, IBM Cloud Division
Alan Southall, SVP of Engineering, Head of IoT Predictive Maintenance, SAP
David Friend, CEO, BlueArchive
Wednesday, March 1, 2017
The IPlytics Platform is an intelligence IP analytics SaaS to analyze patent strategy, technology trends, market developments and a company’s competitive position using the innovative big data & machine learning techniques.
If you are interested in the IPlytics Platform, please contact Alex G. Lee (email@example.com).
Monday, February 6, 2017
The enormous costs of unsuccessful IoT innovation R&D projects are often scrutinized. TechIPm patent research offers a way to decrease the risk of failures and its high costs.
Saturday, January 7, 2017
IoT + Big Data + AI + 3D Printing became the key enabling CE technologies
AR/VR Products are widely adopted in CE market
Robots became an essential part of smart home
Drone became a mainstream CE business
Industry crossover and convergence will be accelerated
Monday, January 2, 2017
For a Free Webinar
Contact us to find out more how we can also help you with a sharp Analysis, Seminar & Training!
Panel discussion about the role of IP in the IoT community
As Panellists, we welcome Joyce Deuley (CEO & Founder Smart Texas Alliance), Kurt Kelley (CEO& Founder Excelerated Technology Consultants), Dr Alex G. Lee (Founder TechIPm and Managing Partner Liquidax Capital)
What this panel is about
In this panel, we will hear about the application of patents in IoT from Joyce Deuley, Kurt Kelley will discuss the dangers of IP when utilizing 3rd party services to build your total solution and Dr Alex G. Lee will cover several topics on IoT innovation and IoT + Big Data + AI integration strategy insights form patents, IP-based IoT innovation platform for business growth. After the panellists gave an insight into their topics, you will have the opportunity to join the open discussion where you will be able to ask questions and discuss some points directly with the panellists.
About the Speakers
Joyce Deuley: As an IoT analyst and content strategist, Joyce has spent the better part of the last five years examining IoT market trends, challenges and opportunities, and sharing the impact of what the IoT has to offer. Currently, Joyce is the Founder & CEO of a Texas-based, state-wide non-profit, the Smart Texas Alliance, that is looking to promote and elevate the IoT community in order to make Texas a “Smart State” via education, partnership development, and community engagement.
Kurt Kelley: As CEO of his Technology Consultancy, Kurt specializes in developing relationships between carriers, re-sellers, and industry leading technology providers globally to solve real business challenges. Before founding Excelerated he served in multiple capacities at Verizon, and most recently Stream Technologies where he was responsible for managing the IoT re-sellers and vertical solution providers. With over twenty years of technology experience there is rarely a problem he is unable to organize an end to end solution for.
Dr Alex G. Lee: Alex brings over 25 years of unique experiences and expertise in consulting on business strategy, IP management, technology commercialisation and many more.Some leading companies and research institutions that Dr Lee has worked with include Samsung, Korea Telecom, KMW, MIC Radio Research Laboratory, Boston University, and Georgia Tech. Dr Lee has also founded and managed several companies and industry organizations such as TechIPm, LLC for IP strategy consulting, Xanadu Big Data, LLC for the big data technology licensing and commercialization, and u-City Forum for the IoT smart city development through public-private partnership and is now participating in the MIT Sloan School of Management Executive Program for strategy and innovation.
Registration URL: https://attendee.gotowebinar.com/register/4238486862931738114
Attention: Please register with your professional email account. We cannot allow attendees to sign up with private accounts (such as yahoo or gmail accounts)
Friday, December 30, 2016
IoT Connected Health Patents Data 4Q 2016 is a custom research of TechIPm, LLC (www.techipm.com) based on the analysis of the published patent applications and issued patents in the USPTO regarding the IoT (Internet of Things) connected health.
1. Search for the IoT connected health related patents.
Search the USPTO database for the IoT connected health related published patent applications and issued patent as of 4Q 2016
2. Review the searched patents for the key IoT connected health patents.
Categorize the identified patents by the key connected health application system:
Clinical Health Management System, Fitness/Workout Management System, Health ICT System, Home Healthcare System, Medication Management System, Personal Health Management System, Physical Activity Monitoring System, Physiological Monitoring System, Sleep Monitoring System, Smart Cloth/Footwear, Telemedicine System
Categorize the identified patents by the key connected health value chain player:
Consumer Electronics Manufacture, Consulting Service, Financial Service, Healthcare Service, Healthcare Solution, ICT Solution, Medical/Health Device Manufacture, Patent Monitization Entity, R&D (including university, individual inventor), Semiconductor Device Manufacture, Sports Goods/Equipment Manufacturer
Categorize the identified patents by the key connected health technology innovation:
Activity Monitoring Automation, Healthcare Information System, Healthcare Network System, Intelligent Medical Diagnosis/Treatment, Personal Health Management, Personalized Medicine, Physiological Information Sensing, Remote Health Monitoring
MS excel file for current assignee, patent number (hyperlinked to Google Patent), title, application system category, value chain player category, technology innovation category
Examples for Data Use Cases
Patent information can provide insights regarding the state of the art of connected health innovations.
Using patent information, one can identify the potential innovation R&D areas (“white space”) that can lead to new connected health products/services development through the patent analysis.
Patent information can provide insights regarding the competitive advantage innovation strategy in alignment with the strategic move of a specific company for connected health business leadership through the cross-competitor analysis.
Patent information can provide insights regarding the state of the art of connected health innovations of the value chain players.
Patent Dispute Risk
Patent information can provide insights regarding the potential patent dispute risks of connected health applications.
For more information, please contact Alex G. Lee at firstname.lastname@example.org .