The document discusses the E-Track project which aims to develop a next generation animal tracking system using satellite navigation. The system will have high precision tracking, detect animal behavior, and include tags, data acquisition tools, and data analysis tools. It will be tested on birds and mammals. The system will reduce tracking data to identify behaviors of interest to biologists like resting, foraging and social behaviors. It discusses current GNSS tracking practice and challenges in balancing tag weight with sampling needs while integrating EGNOS satellite navigation.
Animal behaviour analysis with GPS and 3D accelerometersTamme van der Wal
Presentation delivered at European Conference for Precision Livestock Farming at 11 September 2013 by Andrew Spink. How GPS and 3D accelerometers help in sensing and analysing different animal behaviours.
Use of satellite imagery for the generation of an aquaculture atlas : a case ...Blue BRIDGE
Presented by Nicolas Longépé of CLS at the BlueBRIDGE Workshop at SeaTech Week in Brest, France, October 13th, 2016.
http://www.bluebridge-vres.eu/events/join-bluebridge-10th-biennial-sea-tech-week-brest-france
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/cadence/embedded-vision-training/videos/pages/may-2014-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Chris Rowen, Fellow at Cadence, presents the "Taming the Beast: Performance and Energy Optimization Across Embedded Feature Detection and Tracking" tutorial at the May 2014 Embedded Vision Summit.
This presentation looks at a cross-section of advanced feature detectors, and considers the algorithm, bit precision, arithmetic primitives and implementation optimizations that yield high pixel processing rates, high result quality and low energy. Rowen also examines how these optimization methods apply to kernels used in tracking applications, including fast connected component labeling. From this Rowen derives general principles on the priority and likely impact of different optimization types.
Animal behaviour analysis with GPS and 3D accelerometersTamme van der Wal
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Use of satellite imagery for the generation of an aquaculture atlas : a case ...Blue BRIDGE
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http://www.bluebridge-vres.eu/events/join-bluebridge-10th-biennial-sea-tech-week-brest-france
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/cadence/embedded-vision-training/videos/pages/may-2014-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Chris Rowen, Fellow at Cadence, presents the "Taming the Beast: Performance and Energy Optimization Across Embedded Feature Detection and Tracking" tutorial at the May 2014 Embedded Vision Summit.
This presentation looks at a cross-section of advanced feature detectors, and considers the algorithm, bit precision, arithmetic primitives and implementation optimizations that yield high pixel processing rates, high result quality and low energy. Rowen also examines how these optimization methods apply to kernels used in tracking applications, including fast connected component labeling. From this Rowen derives general principles on the priority and likely impact of different optimization types.
Activity recognition based on a multi-sensor meta-classifierOresti Banos
Ensuring ubiquity, robustness and continuity of monitoring
is of key importance in activity recognition. To that end, multiple sensor con gurations and fusion techniques are ever more used. In this paper we present a multi-sensor meta-classi er that aggregates the knowledge of several sensor-based decision entities to provide a unique and reliable activity classi cation. This model introduces a new weighting scheme which improves the rating of the impact that each entity has on the decision fusion process. Sensitivity and speci city are particularly considered as insertion and rejection weighting metrics instead of the overall accuracy classi cation performance proposed in a previous work. For the sake of comparison, both new and previous weighting models together with feature fusion models are tested on an extensive activity recognition
benchmark dataset. The results demonstrate that the new weighting scheme enhances the decision aggregation thus leading to an improved recognition system.
This presentation illustrates part of the work described in the following articles:
* Banos, O., Damas, M., Pomares, H., Rojas, F., Delgado-Marquez, B. & Valenzuela, O.
Human activity recognition based on a sensor weighting hierarchical classifier.
Soft Computing - A Fusion of Foundations, Methodologies and Applications, Springer Berlin / Heidelberg, vol. 17, pp. 333-343 (2013)
* Banos, O., Damas, M., Pomares, H., Rojas, I.: Activity recognition based on a multi-sensor meta-classifier. In: Proceedings of the 2013 International Work Conference on Neural Networks (IWANN 2013), Tenerife, Spain, June 12-14, (2013)
Using Touchscreen Operant Systems to Study Cognitive Behaviors in RodentsInsideScientific
In this exclusive webinar sponsored by Lafayette Instrument, experts discuss novel rodent Touchscreen systems, referred to as Bussey-Saksida Systems, in terms of the animal environment, various behavioral Tasks, data analysis, methodology and prescribed best practices. In addition, information on integrating Touchscreen behavioral Tasks with video tracking, optogenetics and electrophysiology is shared.
Background Information:
Translational neuroscience has driven the need to create validated rodent and primate touchscreen ‘Tasks’ that are designed to mimic similar tests in clinical research. These Tasks cover many different aspects of cognitive behavior, one such example being PAL (Paired Associate Learning), a task shown to be very sensitive to detecting early onset of Alzheimer’s disease in humans. This well established human task displays six different images in six locations on a touchscreen -- the subject has to remember where each image was shown. If a mistake is made the images are shown to the subject again, introducing learning memory into the Task.
In the rodent version of the Task, subjects are first trained to touch the screens, then to initiate a task, and finally to learn which locations each of three images belong. The animal environment is optimized to focus subject attention to the Task displayed. In addition, to better understand the cognitive processes at play in the touchscreen Tasks these systems have been further developed to integrate behavioural tests with either Electrophysiology recording, optogenetic stimulation or video tracking.
A pharmaceutical product that is intended to enhance visibility throughout the Supply Chain. RFID Systems are used throughout Supply Chains. Since RFID Systems have a tag-reader infrastructure, a tagged asset has to be within 10 feet of a reader for the data to be read and sent to a cloud. This limitation causes many in-transit problems with counterfeit or tampered product entering the Supply Chain and millions of dollars are lost. We use a tiny, cost-effective, GPS tag to track assets in-transit giving you an end-to-end security program.
Embedded Sensing and Computational Behaviour ScienceDaniel Roggen
Overview of the activities in the Sensor Technology Research Centre, University of Sussex, UK, in wearable technologies and computational behaviour science.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2014-member-meeting-sensor-platforms
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Kevin Shaw, Chief Technology Officer at Sensor Platforms, delivers the presentation "Using Inertial Sensors and Sensor Fusion to Enhance the Capabilities of Embedded Vision Systems" at the May 2014 Embedded Vision Alliance Member Meeting.
Citron : Context Information Acquisition Framework on Personal DevicesTetsuo Yamabe
Tetsuo Yamabe, Ayako Takagi, and Tatsuo Nakajima. 2005. Citron: A Context Information Acquisition Framework for Personal Devices. In Proceedings of the 11th IEEE international Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA’05, full paper)
Thank You for referencing this work, if you find it useful!
Reference/Citation: Selim Ickin, Katarzyna Wac, Markus Fiedler, Lucjan Janowski, Jin-Huyk Hong, Anind K. Dey, Factors Influencing Quality of Experience of Commonly-Used Mobile Applications. IEEE Communications Magazine (IEEE COMMAG), Special Issue on QoE Management in Emerging Multimedia Services, 50(4): 48-56, IEEE Press, April 2012.
Robotic assistance for the visually impaired and elderly peopletheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Robotic assistance for the visually impaired and elderly peopletheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Activity recognition based on a multi-sensor meta-classifierOresti Banos
Ensuring ubiquity, robustness and continuity of monitoring
is of key importance in activity recognition. To that end, multiple sensor con gurations and fusion techniques are ever more used. In this paper we present a multi-sensor meta-classi er that aggregates the knowledge of several sensor-based decision entities to provide a unique and reliable activity classi cation. This model introduces a new weighting scheme which improves the rating of the impact that each entity has on the decision fusion process. Sensitivity and speci city are particularly considered as insertion and rejection weighting metrics instead of the overall accuracy classi cation performance proposed in a previous work. For the sake of comparison, both new and previous weighting models together with feature fusion models are tested on an extensive activity recognition
benchmark dataset. The results demonstrate that the new weighting scheme enhances the decision aggregation thus leading to an improved recognition system.
This presentation illustrates part of the work described in the following articles:
* Banos, O., Damas, M., Pomares, H., Rojas, F., Delgado-Marquez, B. & Valenzuela, O.
Human activity recognition based on a sensor weighting hierarchical classifier.
Soft Computing - A Fusion of Foundations, Methodologies and Applications, Springer Berlin / Heidelberg, vol. 17, pp. 333-343 (2013)
* Banos, O., Damas, M., Pomares, H., Rojas, I.: Activity recognition based on a multi-sensor meta-classifier. In: Proceedings of the 2013 International Work Conference on Neural Networks (IWANN 2013), Tenerife, Spain, June 12-14, (2013)
Using Touchscreen Operant Systems to Study Cognitive Behaviors in RodentsInsideScientific
In this exclusive webinar sponsored by Lafayette Instrument, experts discuss novel rodent Touchscreen systems, referred to as Bussey-Saksida Systems, in terms of the animal environment, various behavioral Tasks, data analysis, methodology and prescribed best practices. In addition, information on integrating Touchscreen behavioral Tasks with video tracking, optogenetics and electrophysiology is shared.
Background Information:
Translational neuroscience has driven the need to create validated rodent and primate touchscreen ‘Tasks’ that are designed to mimic similar tests in clinical research. These Tasks cover many different aspects of cognitive behavior, one such example being PAL (Paired Associate Learning), a task shown to be very sensitive to detecting early onset of Alzheimer’s disease in humans. This well established human task displays six different images in six locations on a touchscreen -- the subject has to remember where each image was shown. If a mistake is made the images are shown to the subject again, introducing learning memory into the Task.
In the rodent version of the Task, subjects are first trained to touch the screens, then to initiate a task, and finally to learn which locations each of three images belong. The animal environment is optimized to focus subject attention to the Task displayed. In addition, to better understand the cognitive processes at play in the touchscreen Tasks these systems have been further developed to integrate behavioural tests with either Electrophysiology recording, optogenetic stimulation or video tracking.
A pharmaceutical product that is intended to enhance visibility throughout the Supply Chain. RFID Systems are used throughout Supply Chains. Since RFID Systems have a tag-reader infrastructure, a tagged asset has to be within 10 feet of a reader for the data to be read and sent to a cloud. This limitation causes many in-transit problems with counterfeit or tampered product entering the Supply Chain and millions of dollars are lost. We use a tiny, cost-effective, GPS tag to track assets in-transit giving you an end-to-end security program.
Embedded Sensing and Computational Behaviour ScienceDaniel Roggen
Overview of the activities in the Sensor Technology Research Centre, University of Sussex, UK, in wearable technologies and computational behaviour science.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2014-member-meeting-sensor-platforms
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Kevin Shaw, Chief Technology Officer at Sensor Platforms, delivers the presentation "Using Inertial Sensors and Sensor Fusion to Enhance the Capabilities of Embedded Vision Systems" at the May 2014 Embedded Vision Alliance Member Meeting.
Citron : Context Information Acquisition Framework on Personal DevicesTetsuo Yamabe
Tetsuo Yamabe, Ayako Takagi, and Tatsuo Nakajima. 2005. Citron: A Context Information Acquisition Framework for Personal Devices. In Proceedings of the 11th IEEE international Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA’05, full paper)
Thank You for referencing this work, if you find it useful!
Reference/Citation: Selim Ickin, Katarzyna Wac, Markus Fiedler, Lucjan Janowski, Jin-Huyk Hong, Anind K. Dey, Factors Influencing Quality of Experience of Commonly-Used Mobile Applications. IEEE Communications Magazine (IEEE COMMAG), Special Issue on QoE Management in Emerging Multimedia Services, 50(4): 48-56, IEEE Press, April 2012.
Robotic assistance for the visually impaired and elderly peopletheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Robotic assistance for the visually impaired and elderly peopletheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
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Satellite Navigation for Behaviour Analysis
1. SatelliteNavigation
for
BehaviourAnalysis
Tamme van der Wal (AeroVision)
Andrea Kölzsch (NIOO-KNAW)
Lucas Noldus (Noldus IT)
2. E-Track: the project
Next generation GNSS animal tracker:
• High precision;
• Detecting and analysing animal behaviour;
• An end-to-end system:
– Tags (EGNOS enabled);
– Data acquisition tools;
– Data visualisation tools;
– Data analysis tools;
• Test on birds and mammals;
• Demonstrate commercial feasibility.
6-4-2012 E-Track 2
3. Frommovement tracks to
behaviouralpatterns
Data reduction & distillation:
Position-Velocity-Time (PVT) relevant behaviour:
• Good enough spatial resolution;
– Better than 1 meter;
• Good enough temporal resolution;
– Better than once per 5 minutes sampling;
• All conditions – also wooded / hilly terrain.
6-4-2012 E-Track 3
4. Examples of relevant behaviour
Automatic detection: Biologists interest:
• (Home range („extent‟ / Utilisation • Walking
function)) • Resting/sleeping
• Locomotion (e.g. distance • Foraging
moved, velocity, acceleration)
• Exploring a new region
• Spatial behaviour (zone
entry/exit, time in zone, distance to • Escaping from a predator
zone/point, zone transition, heading to • Flying short distances
point)
• Flying long distances/fast =
• Path shape (turn angle, heading)
migration
• Body
• Mating
posture, orientation, behaviour
pattern • Swimming, diving
(mobility/immobility, stop/walk/run, stand • Preening ...
/lie, grazing, rotation)
• Social behaviour (relative distance:
in proximity, contact; relative movement:
move towards, move away from)
6-4-2012 E-Track 4
7. What is it all good for?
• Incidents (collisions, damage etc.);
• Explanation of behaviour impacts;
• Interaction with environment;
• Social behaviour;
• Deviating behaviour;
• Spatial planning;
• Real Time Guidance / Correction / Instruction.
6-4-2012 E-Track 7
13. GNSS EGNOS
-“DGPS is expensive”
-“DGP … what??”
-“Tag becomes too heavy”
-…
6-4-2012 E-Track 13
14. EGNOS or EDAS
EuropeanGeostationaryNavigationOverlay Service
EGNOS Data Access Service (EDAS)
6-4-2012 E-Track 14
15. User Requirements
• The position of the animal:
– < 1 meter (absolute or relative?); < 5 minutes;
– EGNOS and/or EDAS (post processing);
• Data reception:
– Download opportunities (GPRS, Argos/Iridium, …);
• Additional sensors:
– Accelerometer
– Proximity detector
• Software: Integrated
– Data processing, (re)formatting
– Visualisation
– Annotation
– Standard/up-to-date algorithms
– DYO analyses
6-4-2012 E-Track 15
16. E-Track
CHALLENGES:
• Balance tag weight with
expectations of sampling
frequency and accuracy;
• Integrating EGNOS – in
particular in “wildlife
environments”;
• Developing an end-to-end
system (plug&play?
mix&match?
6-4-2012 E-Track 16
17. Thankyouforyour attention.
Meet us at:
E-Track is carried out in the context of the Galileo FP7 R&D programme
supervised by the GSA. (nr. 277679-2). For more information, please check
www.etrack-project.eu .
6-4-2012 E-Track 17
