IOT Deployed PPI. Montgomery County, MD Thingstitute A case study of three test environments
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1 IOT Deployed PPI Montgomery County, MD Thingstitute A case study of three test environments
2 What problems exist in IoT? Scalability How many devices can be communicating? Sustainability How long can a device talk? Replicability How difficult is it to get the environment running? Security Who can read the data? Who can activate devices?
3 IOT as the Central Nervous System Cloud receives information and sends out commands Network relays information from sensors to cloud, and cloud to actuators Sensors detect information at the edge, actuators affect the environment H. Ning and Z. Wang, "Future Internet of Things Architecture: Like Mankind Neural System or Social Organization Framework?," in IEEE Communications Letters, vol. 15, no. 4, pp , April 2011.
4 1. Adapted from original work by Mariana Ruiz 2. By Thomas Splettstoesser ( - Own work, CC BY-SA 4.0 Communications as Synapses Axon Dendrite Electrical Synapse Faster Bi-directional Adapt to long-term environment Chemical Neurotransmitter Can produce signal gain Excitatory and inhibitory
5 Reflex Arc FOG Computing Edge Computing (FOG) Pushing cloud-like analytics to the edge Cutaneous Reflex Arc - Instantaneous Reactivity - Adaptive Locomotion Retinal Signal Processing - Sensor adaptivity and fusion
6 Sensor Data Actuator Status Bio-Feedback Sensor Adaptation Sensor Adaptation Cloud Network Gateway Sensor/Actuator Actuator Commands Vestibulo-Ocular Reflex By User:Mikael Häggström - Image:ThreeNeuronArc.png. Original uploader was Tvil at en.wikipedia, CC BY-SA 3.0
7 Biologically Inspired IoT Architecture Intelligent Fault Aware Routing Compressed/ Fused Data Data/ Events Cloud Network Smart Gateway Sensor/Actuator Intelligent Fault Aware Routing Feedback for Model learning Sensor Adjustment Actuator Triggers
8 Biologically Inspired IoT Architecture Promotes Scalability Data concatenation prevents network saturation Promotes Replicability Model is well understood Networks protocols can adapt
9 Analog vs. Digital
10 Analog vs. Digital Digital Accuracy dependent upon range and bits Accuracy and power are direct tradeoffs Discrete set of values Robust Analog Not replicable across connectivity Continuous set of values Efficient
11 Why Analog Edge Sensors? Digital CMOS technology approaching fundamental limits 5nm transistor gate technology 20 silicon molecules wide Digital power consumption based on voltage and clock frequency P CV 2 f Analog Cognitive Computing capable of fast, low power pattern recognition Also called Neuromorphic Engineering
12 High-Resolution digital sensing isn t sustainable Knud Lasse Lueth, IoT Analytics. IoT Market Forecasts at a glance
13 Micro-Energy Harvesting Derive energy from ambient sources Solar, kinetic, geothermal, piezoelectric, etc Can enable sustainable, near perpetual operation of connected sensors
14 Analog counterparts are more efficient Analog Retina - Motion Flow on microcontroller And could be powered from microharvesting
15 Components of a Scalable and Sustainable Bio-Inspired IoT Deployment Power efficient edge sensors Plan for analog-front-end sensors FOG computing to concatenate data Also provide direct M2M communication Network topology aware smart gateways Cloud and Service layer performs high-level tasks Bi-directional communication for sensor adaptation and feedback
16 What are the problems with this model? Real-world IoT deployments are heterogeneous Most deployments use an array of manufacturers and technologies Many partners have IP protected layers Device types are numerous and have varied interfaces No standard for temperature, humidity, gas sensing, etc.. Some technologies are not mature LoRa and 6LoWPAN technologies are still in early stages
17 The Thingstitute Architecture Cloud Network Smart Gateway Primary Secondary Azure Everyware Cloud/ ThingWorx Sensor/Actuator Data Sources Earth Networks / Senseware / REST APIs
18 The Thingstitute Architecture Cloud Network Smart Gateway Transmission Technologies Sensor/Actuator Protocols REST:HTTP
19 Data in Motion Exchange Internal pub/sub broker for multiple protocols Prevents lock-in Heterogeneous cloud deployment
20 The Thingstitute Architecture Cloud Network Smart Gateway Sensor/Actuator
21 The Thingstitute Architecture Cloud Network Smart Gateway Sensor/Actuator Commercial: Off-The-Shelf: Custom: N5 Sensors
22 Communications and Power are varied Not-Guaranteed Typically Wi-Fi LoRa or Optical Bandwidth Limited Cellular Communications Guaranteed, Poor signal propagation
23 SCALE: Senior Living Facility Use Cases Environmental and Air Quality Monitoring Done Fall Prevention and Detection Silver Alert Prevention Medication Tracking, etc Challenges: Not guaranteed internet access Sensing medical data is sensitive Privacy and Security
24 Living Community Showcase: Transportation Use Cases: Improve Ridership Experience to capture riders Bus Arrival Time Security Comfort Vehicle-to-Infrastructure Playground Early adoption of V2I technologies in emulated system Bus and Bus-Stop as a Platform Challenges: Public Policy and Union Efficient Bandwidth usage
25 Smart Agriculture Use Cases: Land Utilization and Crop Yield Animal health tracking Improve Pick-your-own experience Urban Agriculture Challenges: Connectivity and power Determining proper actuation of data for precision agriculture
26 IOT Deployed PPI More Information: Website:
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