Sistemi rinconfigurabili a basso
consumo per il monitoraggio
distribuito
Tutor: prof. Luca Benini
Outline
Wireless Video sensor Node
Wireless Video sensor Network, WVN
Power issue
Energy Harvesting
PIR Sensor
Multomodal low cost system
Application of video surveillance
Wireless Video Sensor Network (WVSN)
WSN with cameras for ambient monitoring
Unobtrusive
No cables (remote locations)
Power availability issue
Battery powered
Sustainable operation
Processing
Wireless communication
Multimodal surveillance networks
Augment information
Reduce power consumption
Energy harvesting techniques to extend node lifetime
Power issue
Energy consumption issue
Image acquisition and processing
Wireless transmission of recorded transmission
Several techniques can be used to extend
network lifetime
Multimodal surveillance
Energy harvesting
Local processing of images
Resource Manger
Energy efficient
Multimodal sensing
Energy harvesting
Local computation
Energy efficient Wireless Video Sensor Node
Combines three modalities
A Pyroelectric InfraRed (PIR) sensor provides a low
power wake up signal. Sensor sensibility is modulated
according to available energy and image contrast.
A PhotoVoltaic (PV) module is used to harvest energy
from the environment.
Images are locally classified using Support Vector
Machines (SVM) to detect relevant event and limit
wireless transmission of undesired images
Wireless Video Sensor Node
Samrt Camera =Camera + intelligence
The basis for new applications
Such as: detection, tracking, scene analysis
APPLICATIONS:
• Automotive
• Mobile Comm.
• Surveillance
• Consumer
Wireless Video Sensor Node –
(II)
Low cost
Low power consumption
Local "intelligence" (on-board image
processing capability)
A reconfigurable architecture to achieve
flexibility
Wireless connectivity
Increase battery live
Wireless Video Sensor Node –
(III)
Processing unit
Technology
Processor approach:
DSP,
Media Processor,
GPU,
ARM
Programmable Logic
approach:
CPLD,
FPGA,
Application
with
smart
camera
People Detection
MICRO Current Frame BackgroundSubtraction Winows Transfer Feature Extraction Embedded Support Vector Machine(ERSVM) Background FPGA
Application –
People detection II
ARM9 – STR912
¾
Three frame difference: background subtraction
¾
Region of Interest (ROI) detection (128x64 pixels)
¾
Feature extraction: average gray value over column and row (192 features)
Sensor conditioning circuits: band pass filter
(0.2-12Hz) + amplifier (1500x) + trigger
generator
Low power: 1.5mW
Detects changes in incident IR radiation
Moving bodies
PIR output dependencies
Speed
Temperature
Distance
Sensors PIR
+ + Out Vdd GND Sensitive elements Lens array Incident radiation Absorbing structureTypical use of PIR Sensor
VIDEO
PROCESSING
Wireless
Transceiver
2.4GHzSLEEP MODE
Application III –
abandoned /removed
object detection with PIR Sensor
Active without video sensor
NO EVENTS! Sleep mode, only
PIR active
…
…
EMPTY SCENE PIR->START VIDEO PROCESSING
Application IV –
ZigBee WSN
PIR-CAMERA
•
Zibgee comunication
•
Scalable topology
Application IV –
ZigBee WSN
PIR-CAMERA
Power consumption measurement
Extended battery life
Energy Harvesting &
MPC ( ETH-
ZURICH)
•
Model Predictive Control for rates and other
parameters
•
Distributed MPC
•
Control the PIR sensitivity
Resource Manager for embedded system (SCALOPES
EU PRPJECT & STM)
Hw Design &
Implementation
Thermal sensor
Power Islands
Clock gating
Clock scaling
Sw Design
Porting of the Linux
RM layer on SPEAr
platform
Adding RM feature to
the IPs driver
SPEAR ARCH-DRIVER Normal Mode Slow Mode Doze Mode Sleep Mode Freq. of Cores Freq of DDR Freq of Perif CPUIDLE CPUFREQ ACPI-DRIVER RM-DRIVER GOVERNORS GENERIC INFRASTRUCTURE SPECIFIC SPEAR GOVERNOS USER LEVEL INTERFACES APPLICATIONS/ SURVEILLANCE APPLICATION •/sys/devices/system/cpu/cpuidle •/sys/devices/system/cpu/cpufreq
•
Objective
:
A Linux-based RM infrastructure for the configurable
SPEAR platform
(multi-core processor + domain specific configurable
Collaborations
PROJECTS
EU PROJECT:
Scalopes ‘09-’10
SensactionAAL ‘08 – ‘09
National PROJECT:
SUMMIT ‘07-’08
PRIIN
Industrial
STMicroelectronics ( Microcontroller, Vision, SCALOPES)
Datalogic ( wireless applications, SUMMIT)
Accademic
ETH – Zurich ( 6 months intership) (MPC & Energy harvesting)
EPFL (Andrea Acquaviva - reconfigurable architecture )
University of Trento ( Support Vector Machine)
PoliMI ( SCALOPES porjects)
Publication
Journals:
Transactions on HiPEAC-1, Lecture Notes in Computer Science (LNCS),
Springer-Verlag Berling Heidelberg New York Titolo: Exploration of Reconfiguration Strategies for Environmentally Powered DevicesAutori: Alex E. Susu, Michele Magno, Andrea Acquaviva, David Atienza, Giovanni De Micheli
Rivista: Journal of Real-Time Image Processing Titolo: A low-power wireless video sensor
node for distributed object detectionAutori: Aliaksei Kerhet, Michele Magno, Francesco Leonardi, Andrea Boni and Luca Benini
Conferences:
Congresso: Advanced Video and Signal based Surveillance Titolo: Distributed Video Surveillance Using Hardware-Friendly Sparse Large Margin Classifiers Autori: Aliaksei Kerhet, Francesco Leonardi, Andrea Boni, Paolo Lombardo, Michele Magno, Luca Benini
Luogo: Londra Data: Settembre 2007
Congresso: 11th EUROMICRO Conference on Digital System Design Titolo: A Solar-powered Video Sensor Node for Energy Efficient Multimodal SurveillanceAutori: Magno, Michele; Brunelli, Davide; Zappi, Piero; Benini, LucaLuogo: ParmaData: Settembre 2008
Congresso: Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications (M2SFA2) Titolo: Multi-modal Video Surveillance aided by Pyroelectric Infrared Sensors Autori: Michele Magno; Federico Tombari; Davide Brunelli; Luigi Di Stefano; Luca Benini Luogo: Marsiglia Data: Ottobre 2008
Publication
(II)
Congresso: Sixth IEEE International Conference on Advanced Video and Signal Based
Surveillance Titolo: Multimodal Abandoned/Removed Object Detection for Low Power Video Surveillance SystemsAutori: Michele Magno; Federico Tombari; Davide Brunelli; Luigi Di Stefano; Luca BeniniLuogo: GenovaData: Settembre 2009
Congresso: Third ACM/IEEE International Conference on Distributed Smart Cameras
(ICDSC 2009) Titolo: Adaptive Power Control for Solar Harvesting Multimodal Wireless Smart Camera Autori: Michele Magno, Davide Brunelli, Lothar Thiele and Luca Benini Luogo: Como
Data: Agosto 2009
POSTERS:
Congresso: International Conference on Distributed Smart Cameras Titolo: A Low-Power
Configurable Wireless Video Sensor Node for Distributed Vision Applications Autori: MAGNO M., L. BENINILuogo: Vienn aData: Settembre 2007
Congresso: Fifth European conference on Wireless Sensor Networks, EWSN 2008 Titolo: A
Self-powered Video Node Triggered by PIR Sensors Autori: M. Magno, D. Brunelli, P. Zappi and L. Benini Luogo: Bologna Data: Gennaio 2008
Congresso: 6th European Conference on Wireless Sensor Networks Titolo: Detection of
abandoned/removed objects with a video sensor node aided by Infrared Sensor Autori: Michele Magno, Davide Brunelli, Luca Benini Luogo: Cork, Ireland Data: Febbraio 2009
Publication
(III) –
Work in progress
Congresso: The 9th ACM/IEEE International Conference on Information Processing in Sensor
Networks (IPSN2010) Titolo Energy Efficient Cooperative Multimodal Ambient Monitoring Autori: Magno M., Zappi P., Brunelli D., L. BENINI
STATUS: Submitted
TITOLO: Energy aware multimodal video surveillance embedded system. Autori: Magno M., Lanza A. Brunelli D., Di Stefano L., Benini L.
TITOLO: Resource manager for video surveillance embedded system. Autori: Magno M., Brunelli D., Benini L.