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The IoT Conversation

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A presentation given at Thingmonk 2016 on Thington and what IoT can learn from other technologies

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The IoT Conversation

  1. 1. Matt Biddulph Thington Inc @mattb Continuing the IoT conversation
  2. 2. “It is a magnificent feeling to recognize the unity of complex phenomena which appear to be things quite apart from the direct visible truth.” Albert Einstein Today I’m going to talk about three areas of technology that Internet of Things systems can learn from. On the surface, none of them are IoT technologies.
  3. 3. One of my favourite concepts is the idea of “consilence”, described by Edward O. Wilson. He believes that knowledge can be unified across scientific disciplines. It’s the idea of “the fundamental interconnectedness of all things” as Douglas Adams put it.
  4. 4. Tech number 1: time-oriented data in financial trading
  5. 5. In financial trading, the most valuable data is the freshest data. The value of much financial data declines over time. The same is true of IoT data when we use it to monitor the real world and trigger actions for users.
  6. 6. As Kevin Slavin described in his brilliant talk “How algorithms shape our world” there are buildings in Manhattan full of servers positioned as close as possible to the London transatlantic data cables. There is almost nothing that humans could do in that real estate that would be more valuable than the lowest-possible latency connection that those servers use to trade on.
  7. 7. The need for low-latency correlation, query and response on realtime data is generally known as CEP: Complex event processing. One such open-source system that we used to build Thington is called Esper.
  8. 8. The Devops community has been using CEP tools for its own real-time time-series analysis and alerting for a long time.
  9. 9. “The problems we look at have temporal constraints ranging from: 5 seconds (counters and statistics) to
 1 second (fraud detection) to
 10 milliseconds (user-action reaction) 
 and
 everywhere in between.” Theo Schlossnagle, OmniTI Theo Schnossnagle has described using Esper for its in-memory time-oriented constructs in order to deal with a wide variety of data on behalf of clients at OmniTI.
  10. 10. Change over Time The essence of real-world data is that it describes change over time. This is a fundamental concept for IoT architectures.
  11. 11. Tech number 2: massively-multiplayer online gaming
  12. 12. Some of the most complex realtime systems in the world are group events such as raiding in World Of Warcraft.
  13. 13. The Internet of Things can turn single-player things such as a car with a single owner and set of keys…
  14. 14. ` … into multiplayer objects by adding a small amount of hardware and a service layer such as Zipcar
  15. 15. Games are essentially asynchronous, essentially multi-character / multi-player, and full of conversations.
  16. 16. Early games such as the Monkey Island are brilliant solutions to giving the player a sense of open conversations in the absence of strong AI and processing power
  17. 17. These techniques are still used in modern games such as 80 Days by Inkle Studios
  18. 18. They open-sourced the narrative engine that their designers (not just their developers!) use to create in-game conversation. We have adapted this open-sourced engine to create a conversational interface in Thington.
  19. 19. Human2Machine The essence of games is the human-machine interface. This is a fundamental concept for IoT architectures.
  20. 20. Tech number 3: conversational social media
  21. 21. This is a sketch by Jack Dorsey of an early idea for status updates that became Twitter
  22. 22. “The emergence of @ to mean a reply was a crucial development in Twitter’s history.” “The first-ever hashtag, @-reply and retweet” — qz.com “Early on, its founders struggled over whether the service was primarily for status updates or conversation.” From a simple system of status updates, a number of emergent features were co-created by Twitter’s userbase that formed the axioms of a rich human ecosystem of conversation.
  23. 23. One example of this is when Twitter technical architect Blaine instituted the rules of @reply scoping, meaning that when one user made an @reply to another, only users that followed both users would see the reply. This helped users managed the firehose of content, and is a lovely example of a technical semantic decision changing the nature of an entire product.
  24. 24. Retweets Hashtags Links Cards Polls The same is true of several other emergent Twitter features.
  25. 25. this slide from Raffi Krikorian At Thington we were inspired by a proposal published by Twitter to their developer community that was never implemented: Annotations.
  26. 26. this slide from Raffi Krikorian The idea was to have tweets with “View Source” - that there could be a packet of data underlying any tweet that was defined by the user’s own app (any app that used the Twitter API). We expanded on this idea to create Thington’s timeline view, where smart home devices talk about themselves in human language, but the data underlying each update is always available for use in automation.
  27. 27. Conversation is Collaboration The essence of social media is that humans are really good at collaborating through conversation. This is a fundamental concept for IoT architectures.
  28. 28. Social media: conversation is collaboration Games: human2machine Data: change over time
  29. 29. “The love of complexity without reductionism makes art; the love of complexity with reductionism makes science.” Edward O. Wilson: Consilience
  30. 30. the Internet of Things should be a conversation
  31. 31. https://thington.com
  32. 32. Thanks! Matt Biddulph @mattb
  33. 33. This material is in part based upon work supported by the National Science Foundation under Grant Number (1621491). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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