Freedom of Movement - an IoT concept Time series databases, data visualization in IoT. FOG, EDGE, MQTT, Bluetooth.

1. PRESENTED BY
Freedom of Movement
Richard Leddy
Copious Systems, Owner
Meshes and Relative Motion
www.copious.world

2. PRESENTED BY
Freedom of Movement
https://en.wikipedia.org/wiki/Wireless_mesh_network

3. PRESENTED BY
Richard A. Leddy
• Many years programming since college (allworkandnoplaymakesjackadull-)
– AI Software, Web Software, Business Applications, Educational Software
– Real-time programming for data acquisition: Linux, Arduino, Teensy
– Recent Work (2017 -2018)
• AxiomWare Bluetooth and MQTT Communication Stack Application Framework
• Bioreactor Startup - Device to Web - Full Stack
– Writing: posts and more posts on their way
• Blockchain Consensus, Evolutionary Computation
– Review Courses and Certs (Last Summer):
• Blockchain, AI, Robotics
• Quantum Computing ???
Who am I? Copious Systems - www.copious.world

4. PRESENTED BY
1 Freedom of Movement
User -> Device -> User. What does that mean? Remove control, Remote management,
Sensor continuity
2 Of Meshes and Databases
Device -> Store -> Web Server. Data collection, responsive apps, data availability, Fog,
Edge, Natural data shards.
3 Web Page Visualization
Web Server -> Page View. Reporting requirements.
Agenda:

5. PRESENTED BY
Freedom of Movement
http://localhost:8080/panel-app.html

6. PRESENTED BY
• Remote Control
• Remote Management
• Sensor Continuity
Freedom of Movement
User -> Device -> User
Icons made by: Freepik from www.flaticon.com

7. PRESENTED BY
Remote Control
• Commands Sent to MCU
– Sequence Recording
– Predictable Delayed Response
Remote Management
• Control Parameters
– Sensor Limits
– Schedule Sequences of Operations
Sensor Continuity
• Sensor in Motion
• Gateway in Motion
Freedom of Movement
https://www.arduinolibraries.info/libraries/tiny-cmd-table

8. PRESENTED BY
Two Scenarios Suggest Different Use Cases
• Sensor in Motion
– Measurement Routing
• Crossover Points
• Target Sequence Storage
• Gateway in Motion
– Sensor Entry and Exit
– Measurement Collective
• Topography Formation
Sensor Continuity

9. PRESENTED BY
Sensors in Motion
https://conferences.sigcomm.org/sigcomm/2013/papers/mcc/p15.pdf
https://conferences.sigcomm.org/sigcomm/2012/paper/mcc/p13.pdf

10. PRESENTED BY
Gateways in Motion

11. PRESENTED BY
Of Meshes and Databases

12. PRESENTED BY
• Problems
• Data Collection
• Responsive Apps
• Data Availability
• Cloud, Fog, Edge
• Natural Data Shards
• Database Options
Of Meshes and Databases
Device -> Store -> Web Server
https://www.digitaltrends.com/computing/worlds-smallest-computer-dwarfed-by-rice-grain/

13. PRESENTED BY
The obvious - but should be mentioned
• Data Collection
– Choose a Database
Problems

14. PRESENTED BY
• Responsive Apps
• Characterize Responses
• Provide Data Marshaling
• Manage Connections
• Work in Gangs
• Pathway Assignments
• Pub/Sub
• etc.
Problems

15. PRESENTED BY
Formalize Responses to Sensor Notifications
Code:
dapi.on(“com.axiomware.characteristic.axm_count", dapi.addResponse(AXM_countNotify,(value,format,units) => {
// do whatever...
})
);
dapi.on("com.sensirion.characteristic.humidity", dapi.addResponse(SmartHumi_Notify,(value,format,units) => {
// do whatever...
console.log("RESPOND -- com.sensirion.characteristic.humidity");
console.log(`${value}, ${format}, ${units}`);
})
);
https://www.axiomware.com/

16. PRESENTED BY
• Data Availability
• Sensor Events
• Sensor Streams
• Gathering Intervals
• Merging into Archives
Problems

17. PRESENTED BY
Formalize Responses to Sensor Notifications
Code:
var redis = require("redis"),
redClient = redis.createClient(); // leave it to the module to figure out how to connect
redClient.on("error", function (err) {
console.log("Error " + err);
});
dapi.on("com.sensirion.characteristic.humidity", dapi.addResponse(SmartHumi_Notify,(value,format,units) => {
console.log(`${value}, ${format}, ${units}`);
var humidityOut = formatValue(value,format,units);
// redClient.append(myId(SmartHumi_Notify), `,${timeStamp()} : { humidity: ${humidityOut} }`)
// new way
redClient.xadd(myId(SmartHumi_Notify),`* humidity ${humidityOut}`)
})
);

18. PRESENTED BY
• Cloud, Fog, Edge
• Where to gather data
• When to move data blocks
• Save Time Series Analysis
• Storing Likely Requests
Problems
Taking Networks into Consideration

19. PRESENTED BY
• Natural Shards
• Roving Sensors
• Trajectories
• Not a distributed hash
Problems
Segmented Trajectories
10:00
10:02
10:03
10:06
10:07
10:08
10:16
10:17
10:18
10:19

20. PRESENTED BY
Delivering Long Time Intervals (testing laptops 10K points)
• MongoDB
– One Collection - linear time in number of points
– Part of Document -
• InfluxDB
– Measurements - better speed
• Redis
– One Key - fairly constant delivery time - might need higher clock resolution
– Stream
• Just tried it out
Database Options http://www.copious.world/demos/runtimes.html

21. PRESENTED BY
Web Page Visualization

22. PRESENTED BY
• Reporting Requirements
• Streaming
• Intervals
• State
• Rate of Display
• Display Options
Web Page Visualization
Web Server -> Page View

23. PRESENTED BY
Web Page Display Techniques are not All Equal
• D3
– Interesting DOM Management
– Speedy for Special Use Cases
• But, the exception can be the rule
• Virtual DOM Frameworks (Vue.js e.g.)
– DOM Manipulation with Time Series - Questionable
• Canvas Versions Just a Little Faster
– Great for State Management and Programming Ease
• Hardware Accelerated (Pixi.js - flat WebGL)
– High speed graphics rendering
– Still best to do analysis on the backend
Display Options

24. PRESENTED BY
You can see the difference

25. PRESENTED BY
1 Prefer Redis for Accessing Data
Small, Fast, Easy Formalism.
2 Try to Manage User Expectations but Warm Up Data
Coalesce, Archive, Relocate.
3 Stay Foggy
Analysis near complete data or wholistic trajectories - deliver less data less often.
Conclusions:

26. Thank you!
www.copious.world

27. PRESENTED BY