CCTV in the CLOUD

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  • How can some information be secure if it is available in the cloud
  • Probably, the CLOUD, today, is more of a marketing buzzword than a well defined technological concept
    Asking ten different people what the cloud is, you are likely to get ten or, maybe, eleven different answers
    In the field of electronic security the term has been often abused gaining an inappropriate meaning or, worse, a negative misconception

  • It is not affordable/practical to monitor a large number of cameras both for costs of involved resources and for human inability to cope with prolonged attention. According to research, the average professional operator attention drops to only 40% after only 30 minutes. In case of multiple sites spread in the territory local monitoring is too costly and centralized monitoring becomes a must.
  • In a security system the interesting events worth being looked at or saved are, on average, in the order of minutes per week of a few cameras
  • All the new HD video surveillance cameras installed worldwide in 2013 have produced 413 Petabytes (1 PB = 1000 TB) worth of data and are expected to produce more than double in just four years, expanding to 859 PB in 2017
  • http://www.channel4.com/news/london-bombings-cctv-captures-bombers-before-attack
    http://www.officialconfusion.com/77/investigation/policestatements/180705metinvest.html
    http://www.boston.com/news/nation/washington/articles/2007/08/12/us_doles_out_millions_for_street_cameras/?page=full
  • The belief that the CLOUD is just something related to remote storage is widespread in the security market
    It probably comes from the most common use of the cloud for storing large files, e.g.: File storage/sharing = CLOUD = DropBox
  • Centralized storage is in most cases unpractical and often impossible because of the sheer size of produced data and limitations in available bandwidth
    The mentioned amount is enough to fill 92.1 million single-sided, single-layer DVDs or it’s four times the amount of photo and video data stored on Facebook as of February 2012.
    Transferring and storing large amounts of video to the cloud or to a remote data center is economically unsustainable

  • The surveillance business is adopting several technologies designed to accommodate and mitigate the rising tide of data.

    New data compression algorithms. For example, the High Efficiency Video Coding (HEVC) standard—also known as H.265—has been claimed to double the data compression ratio when compared to H.264.

    Video content analysis (VCA) can be used to filter important events out rather than simply recording continuously.

    Nevertheless recording of HD images will only be feasible locally moving at a central location only important images and metadata produced by VCA and biometrics
  • Only the capacity to normalize security data coming from heterogeneous sources and to correlate the gathered information to be compared against known patterns will allow to extract meaningful results which could be actionable in a timely manner
    It should ideally be possible in widely distributed systems to merge information coming from different providers and organizations

Transcript

  • 1. CCTV in the Cloud By Riccardo Mazzurco (www.linkedin.com/in/mazzurco) Oxymoron or paradigm shift?
  • 2. The CLOUD... what is it?
  • 3. The CLOUD: a foggy concept More of marketing buzzwords than well defined technologies People have different ideas on the meaning of these terms In videosurveillance the term CLOUD have been too often abused
  • 4. Advantages of a CLOUD based infrastructure • No need of in-house computing infrastructure • No need of skilled staff for installation, maintenance and troubleshooting • Reliability. The provider takes care of: – Redundancy – Contuinuity of operations – Backups – Disaster recovery
  • 5. Costs scalability of a CLOUD based architecture • No initial investment • Predictable costs • Pay only what you use/need • Grow or shrink computing power, storage and bandwidth on demand
  • 6. Geography independent Unlimited tenants Accessibility of Cloud Architectures
  • 7. Evolution of CCTV
  • 8. Ever growing number number of cameras Human surveillance is not affordable or feasible
  • 9. A real waste of resources Interesting events are just a tiny part of the recorded video
  • 10. HD CCTV = BIG DATA • Data generated by video surveillance has grown to practically unmanageable amounts
  • 11. Real life case: July 2005 London bombings The recordings were examined for weeks by human operators trying to find a clue in the thousands and thousands hours of footage. Weeks of recordings of hundredths diverse CCTV systems where collected from diverse sources: city center control, shops, banks, etc.
  • 12. CCTV and the CLOUD
  • 13. Common misconceptions CLOUD is not just remote storage or accessing applications via web browser
  • 14. Why cloud storage of video is not viable? Sheer size of produced data Costs of storage and transfer Limited available bandwidth
  • 15. Moving mountains around... … extremely rare, just like a speck of gold lost in tons of rock Miners don’t move mountains of rock around! They bring mining equipment close to where gold ore is dug Meaningful images are…
  • 16. So... what now?!
  • 17. Dealing with Big Data • Cannot rely on significantly more efficient image compression algorithms • Must rely on edge-side storage of high quality HD video • Must use video content analysis (VCA) to filter important footage out (thumbnails or short clips) • Describe meaningful events by means of effectively searchable metadata
  • 18. Extracting interesting information on site Understand locally and communicate only if needed Smart cameras can filter out significant events to reduce the quantity of data streamed to the data center even with limited bandwidth
  • 19. Blob Motion Tracking Tracking & Trajectory Smoke detection Fire detection Face detection Crowd detection Number Plate Recognition Lost and Found Detection Traffic Controls Origin, Blind, Darkness Alarm Panic Detection Available features: The Smart Products What can be done today
  • 20. Accurate image analysis: now possible since it is made on RAW images coming from the sensor Smart Products Internal Architecture Local high resolution storage and external streaming with adaptive bandwidth. Broadband connection not required Bidirectional communication layer, encrypted and automatic. Secure and reliable Internet connectivity Virtualized data centre software with Private or Public Cloud deployment. The control room is everywhere an Internet connection is available
  • 21. Similar problem: the search for Higgs boson CERN - LHC accelerator • Bunches of protons and antiprotons crossing 40 million times per second generate about 20 collisions per crossing totaling about 1 billion collisions per second • The frequency of producing a Higgs boson is extremely rare: once in 1013 = 10 000 000 000 000 interactions or one every 3 hours ATLAS experiment • ~100 million electronic channels • If all data would be recorded, this would fill 100 000 CDs per second, a stack which could reach to the moon and back twice each year. • Online data filtering is then a must • Level 1 trigger filters down to about 75 000 events per second. • Level 2 trigger reduces it to about 2 000 events per second. • The Event Filter then selects for permanent storage about 200 “interesting” events per second.
  • 22. The correct approach • Normalize and correlate information from heterogeneous sources to extract meaningful and actionable results • Merge information from widely distributed different providers and organizations
  • 23. Architectural requirements • Distributed uncompromised information • Hierarchical online filtering • Centralized database indexing with simple and efficient search methods for multiple distributed tenants • Extraction of readily actionable information • Possibility to instruct the devices on the field to execute online and offline queries based on requests issued by tenants in the cloud
  • 24. Database indexing in the cloud • Thumbnails – vehicles, license plates, persons, faces, etc. • Metadata – Number plates, face recognition, etc. • Classification and profiling – Person • Age, Gender, Etnicity, Height • Mood, Facial expressions – Vehicle • Car, Bike, Motorcycle, Bus, Van, RV, Truck • Manufacturer, Model
  • 25. Actionable feedback generation • Correlation – Timestamping (synchronized) – Georeferentiation (Indoor, Outdoor) – Identification • RF, NFC, BLE, wifi, cellular, loyalty card • Voice and Biometrics – Third party databases • Publicly accessible data • Crowdsurced data • Data accessible only by Governmental Entities
  • 26. How to get there • The investments and the time needed to achieve the described scenario are certainly very large • It is important, then, to devise effective ways to normalize, merge and analyze data coming from existing systems preserving most of the prior investments
  • 27. Thanks for your attention Any questions?