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Innovation Opportunities

Seeking innovative solutions for:

  • Blockchain Innovation ExpertXinova requires a subject matter expert to evaluate a next generation blockchain platform that utilizes a unique chain joining capability between multiple blockchains.
  • Free the WaterXinova is seeking ways to manage the watery dough problem so vegetables can be included into sheets of dough and baked like traditional crackers.
  • View all opportunities

Problems are a good thing. 

They lead to real solutions. From real innovators.

They fuel innovators’ drive to invent something totally new, or repurpose old tech for brilliant new applications. These solutions reflect the unique diversity and creativity powering our elite innovator network.

 

Recurring Outlier Network Connection Analysis for RAT Detection

Recurring Outlier Network Connection Analysis for RAT Detection

Solution by: Xinova Innovator, Ezekiel Kruglick, PhD

In this solution, a RAT detection analysis for recurring outlier network connections is proposed. In more detail, this describes a solution that can detect repeated “unusual” connections, when any single machine making unusual numbers of outliers is either compromised or has a user performing something deemed unusual.

Action classification and deviation detection of network devices

Action classification and deviation detection of network devices

Solution by: Xinova Innovator, Dr. Zhen Xiao

Action classification and deviation detection of network devices is proposed for this solution.
This describes a solution that performs traffic analysis and detects device anomalies. IoT devices generally have fixed activity patterns, however, personal devices tend to have diverse actions. By monitoring such patterns, and creating better accuracy of device classification, it is possible to more quickly neutralize an attack due to stricter detection criteria for a variety of devices.

Prediction of certain network events based on active data flow

Prediction of certain network events based on active data flow

Solution by: Xinova Innovators, Dr. Jun Fang and Dr. Xiaodong Wong

In this solution, what is proposed is a method of predicting network events by sending traceable particles and analyzing the flow of such data. This describes how a sensitive file can be broken into fragments that are distributed throughout a network system, and where the fragments are “moved” continuously within the system in a random manner. Unauthorized access to these fragments may actively verify a security situation.

Monitoring Servers Using Comparison of Calculated Versus Observed Power Signatures

Monitoring Servers Using Comparison of Calculated Versus Observed Power Signatures

Solution by: Xinova Innovator, Ezekiel Kruglick, PhD

In this paper, what is proposed is a security method of monitoring networking and computing devices. It describes a way of monitoring these devices by comparing the calculated versus the observed power signatures.

Distributed Computing Power Market

Distributed Computing Power Market

Solution by: Xinova Innovators, Xiaoqi Chen and Dr. Zhen Xiao

In this solution, a unique method of distinguishing real users from bots is proposed. In more detail, this describes an authentication system and method to authenticate human users by the user electing to assist in solving an NP-hard calculation problem that is too costly for bots to perform.

Detecting Separation of Subjects from Their Badge

Detecting Separation of Subjects from Their Badge

Solution by: Xinova Innovators, Shmuel Ur, Itzhak Pomerantz, and Vlad Dabija

This solution describes a method to detect the separation of individuals from their entry badges.
In more detail, this describes how a system can maintain awareness of spectator credentials and issue an alert when an attendee is without a badge, or a badge is without an attendee.

Operations and a Surveillance Scripting Language

Operations and a Surveillance Scripting Language

Solution by: Xinova Innovator, Natalya Segal

In this solution, a powerful tool that allows for efficient operations on large sets of dynamic surveillance information is proposed. In more detail, this describes the implementation of a scripting language that can facilitate responses and reduce times for actionable security challenges.

Unique Feature Extraction for Efficient Communication

Unique Feature Extraction for Efficient Communication

Solution by: Xinova Innovators, Jin Sam Kwak and Ju Hyung Son

This solution describes an efficient method of communication between control room and field agent using unique feature extraction. In more detail, this discloses how to select certain context-dependent features to facilitate describing suspects in a crowd.

Method for Collecting and Making Available Contact Information of Event Spectator

Method for Collecting and Making Available Contact Information of Event Spectator

Solution by: Xinova Innovator, Kevin Williams

This solution describes a method of collecting and communicating directly with spectators at an event location. In more detail, this describes how to make spectator contact information immediately accessible to security control center personnel, and have it available should agents require direct access for questioning and verification purposes.

Method for Detecting People Who are Trying to Fool Security

Method for Detecting People Who are Trying to Fool Security

Solution by: Xinova Innovators, Shmuel Ur

This solution describes a method for distinguishing people who are being evasive. In more detail, this describes how to utilize computers to recognize in people in both human-like and machine-like ways, and compare for discrepancies.

Physiological Reaction Monitoring

Physiological Reaction Monitoring

Solution by: Xinova Innovator, Noam Hadas

In this solution, a method to monitor physiological reactions is proposed. In more detail, this describes a new concept to the software/operator system by which data collected from operators is used as part of the analysis and presentation algorithms, in order to improve response.

Synthesized Emotions of People in the Crowd

Synthesized Emotions of People in the Crowd

Solution by: Xinova Innovators, Mordehai Margalit, Dani Zeevi, and Vlad Dabija

This solution describes a method for quickly assessing crowd sentiment. In more detail, this describes how to highlight important anomalies in images presented of crowds, and identify people that display different emotions than those around them in a way that reduces operational overload.

Using Eye- Tracking to Improve Management of Video Feed - innovators, real, R&D, innovation partner, innovation partnership, innovation strategy consulting, business innovation, generate demand

Using Eye- Tracking to Improve Management of Video Feed

Solution by: Xinova Innovators, Shmuel Ur and Or Zilberman

This solution describes a method of using eye-tracking technology to monitor and manage video feeds from security cameras. In more detail, this describes how video feeds can be managed based on the security personnel’s behavior towards the delivered feeds.

Gaze Focus Detection - innovators, real, R&D, innovation partner, innovation partnership, innovation strategy consulting, business innovation, generate demand

Gaze Focus Detection

Solution by: Xinova Innovators, Noam Hadas

This solution describes an idea in which one can locate several video cameras equipped with red flash lights around the perimeter of the event, looking over the crowd. By subtracting subsequent frames taken with the flash firing or not, it is easy to detect the “red eye” reflection, and by knowing which camera took the image know approximately in which direction every individual in the crowd is looking.

Crowd Sourcing Voice Based Direction Alerts - innovators, real, R&D, innovation partner, innovation partnership, innovation strategy consulting, business innovation, generate demand

Crowd Sourcing Voice Based Direction Alerts

Solution by: Xinova Innovators Shmuel Ur, David Hirshberg, and Ariel Fligler

In this solution, a method to use voice-based direction alerts is proposed. In more detail, a solution is proposed that will enable directing people to safety taking into account the environment conditions including noise, congestion of people and reduced faculties due to stress.

Scene Overlay Projection for Correlating Distinct Cameras - innovators, real, R&D, innovation partner, innovation partnership, innovation strategy consulting, business innovation, generate demand

Scene Overlay Projection for Correlating Distinct Cameras

Solution by: Xinova Innovator, Moti Margalit

In this solution, a method to combine all available image sensors into a coherent picture, which generally creates real challenges, is proposed. In more detail, this describes a method of integrating an overlay projector in conjunction with a video camera.  In one example the overlay projector is a laser based projector which emits a light pattern.

 

Detection of Public Incident by Filming Characteristics without Violating Privacy - innovators, real, R&D, innovation partner, innovation partnership, innovation strategy consulting, business innovation, generate demand

Detection of Public Incident by Filming Characteristics without Violating Privacy

Solution by: Xinova Innovator, Xuefeng Song

In this solution, a method to provide fast detection of possible public incident that would allow for a fast response during a large scale incident is proposed.In more detail, this solution analyzes behavioral characteristics of crowd taking photos/videos (before, during and after) of a possible incident by considering the rough location, direction of focus, and distribution of the crowd, and their cellphones’ location attributes, in a way that protects the privacy of the users.

 

Recruiting Crowd Cameras - innovators, real, R&D, innovation partner, innovation partnership, innovation strategy consulting, business innovation, generate demand

Recruiting Crowd Cameras

Solution by: Xinova Innovators, Yang-Won Jung

In this solution, a method to select/recruit attendees who will participate in the surveillance is proposed. In more detail, a surveillance camera emits RF signal in direction of its field of view. The other camera determines whether it is in the Line of Sight (LoS) of the surveillance camera or not. Also, the other camera determines its facing direction in relation to the facing direction of the surveillance camera. Based on the determination, cameras which will become new surveillance cameras are decided.

Protecting Sports and Other Celebrities Against Stalking at Ad-Hoc Events - innovators, real, R&D, innovation partner, innovation partnership, innovation strategy consulting, business innovation, generate demand

Protecting Sports and Other Celebrities Against Stalking at Ad-Hoc Events

Solution by: Xinova Innovator, David W. Ash

In this solution, the approach described is a method to help protect the next tier of celebrities—those requiring significantly more protection than the average person but not receiving government sponsored security. In more detail, a record is made of which fans are appearing at both the celebrity’s private and public events. An algorithm is provided for determining when particular people are appearing in the vicinity of these events to a degree greater than would be expected just via statistical noise.

925768_A Method for Correlating to a Person His Phone Number - innovators, real, R&D, innovation partner, innovation partnership, innovation strategy consulting, business innovation, generate demand

A Method for Correlating to a Person His Phone Number

Solution by: Xinova Innovator, Shmuel Ur

In this solution, a method to correlate a person to his phone number is proposed. In more detail, this teaches how to tie, using video surveillance, a phone number X to a person Y tracked in an event, using many-to-one matching between people and phones, and filtering down until there is a one-to-one match.

Multi-Camera Occlusion and Sudden-Appearance-Change Detection Using Hidden Markovian Chains - innovators, real, R&D, innovation partner, innovation partnership, innovation strategy consulting, business innovation, generate demand

Multi-Camera Occlusion and Sudden-Appearance-Change Detection Using Hidden Markovian Chains

Solution by: Xinova Innovator, Xudong Ma

In this solution, a new object tracking algorithm using multiple cameras for surveillance applications is proposed. The proposed system can detect sudden-appearance-changes and occlusions using a hidden Markovian statistical model. The experimental results confirm that our system detect the sudden-appearance changes and occlusions reliably.

Connect with Xinova

We are always seeking new problems to solve, as well as innovators and entrepreneurs to help us solve them. Let’s work together to create the future.

Our Worldwide Locations

USA

Xinova
311 ½ Occidental Ave S
Suite 300
Seattle, WA 98104
USA
+1 (206) 800-2678

Japan

Xinova Japan GK
Yaesu Mitsui Building 6F
2-7-2 Yaesu, Chuo-ku
Tokyo 104-0028 Japan
+81-3-6478-6120
xinova.jp

China

Xinova Innovation (Beijing) Consultancy Co. Ltd.
Room 2494, Level 24, Tower 3
China Central Place
77 Jianguo Road
Chaoyang District
Beijing, 100025 China

Singapore

Xinova Asia Pte Ltd.
150 Beach Road
#08-06/08 Gateway West
189720 Singapore
+65 6408 5080

Korea

Xinova Korea
10th floor, Golfzone Tower
735, Yeongdong-daero
Gangnam-gu
Seoul 06072, Korea
+82 2 6952 8840
xinova.co.kr

Australia

Xinova Australasia Pty Ltd.
Level 6, 8 West Street
North Sydney, NSW 2060
Australia
+61 2 8093 4850

India

Xinova India
Suite No 208, 2nd Floor
Survey No 414
PSR Complex
Govinda Reddy (GR) Layout
Bannerghatta Road
Karnataka, 560076, India

Finland

Xinova Finland
Erottajankatu 5 A 4
FI-00130 Helsinki
Finland

Affiliate offices in Tel Aviv & Vienna