The vast majority of Internet of Things (IoT) customers are connecting many pieces of equipment with multiple independent sensors. For these customers, detecting a critical operational event, such as when equipment variability reduces the quality of its output, can be challenging. In this session, you learn how AWS IoT Events makes it possible to easily and cost effectively detect system-wide events and respond with appropriate actions to drive results such as optimizing manufacturing efficiency or improving production quality.

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Detecting and responding to critical
events with AWS IoT Events
Raghu Pillutla
Sr. product manager, AWS IoT Events
Amazon Web Services
S V C 2 0 5
Alexander Witte
Cloud architect
BAI Communications

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Today’s agenda
1. AWS IoT Events overview
2. Top use cases
3. Getting started with AWS IoT Events
4. Demo
5. Customer reference – BAI & Toronto Transit System Wi-Fi network
6. Session survey

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AWS IoT service architecture

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AWS IoT Events
AWS IoT Events is a managed service that continuously monitors data to detect stateful
changes and trigger actions or workflows
Build logic flows to evaluate
incoming telemetry data and detect
equipment or process states
Near real-time, data is processed
through detector models from
multiple sources to trigger outputs
Intelligent notifications automate
workflows to improve productivity
and reduce costly noise
!
Build Monitor Automate

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Simplified development with built-in features
AWS IoT Events reduces infrastructure management by reducing the heavy lifting
Deploy models to scale
infinitely
Automate and apply models to
improve operations
Ingest data from
multiple sources
Combine IoT and non-
IoT data streams
Model stateful logic for
optimization
Simplify complex event
management
Uncover actionable insights
with hierarchies
Receive timely alerts and
reduce noise

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AWS IoT Events use cases
Customer value Service capabilities
Condition monitoring
Reduce complexity of self-managed architectures for
monitoring data streams or complex event processes
with multiple data sources
Monitor inputs from telemetry or stored data to detect
stateful changes in behavior with a fully managed
service, and trigger intelligent actions
Asset maintenance
Manage dispatching of employee resources to remote
locations by reducing false-positive alerts and
notifications that increase costs
Detector models can manage multiple instances using
time-based variables and counters to process data in a
hierarchal group and send critical notifications
Products/services
Monitor and manage workflows based on sensor data
from smart products to create useful workflows and
improve customer experience
Sequentially manage events and trigger actions to
various applications, such as CRM, ERP, or mobile apps,
to provide near real time feedback on product or
service utilization
Anomaly detection
Improve detection of anomalies in process
manufacturing or equipment behavior by analyzing
multiple data sources from disparate or silo systems
Ingest data to create actions using event detector
templates to onboard new devices/sensors and quickly
deploy conditional logic at scale for immediate insights
Intelligent applications
Avoid data saturation charts and graphs by reducing
notification noise, general diagnostic data, and static
metrics
Leverage APIs to stream event detector model instances
and send contextual/stateful updates to dashboards or
applications

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AWS IoT Events for discrete manufacturing
Problem
Complex processes and isolated equipment in
manufacturing rarely aggregate data, which
prevents insights on operational metrics and
leads to a rise in maintenance risk.
Solution
AWS IoT Events simplifies managing a scalable
architecture using “detector models” to monitor
variables, timeframes, and states and determine
appropriate triggers for actionable workflows.
Impact
Reduce costs with preventive maintenance, and
improve workflows by triggering intelligent
notifications to alert stakeholders in near real
time. AWS IoT Events minimizes the need for
coding, provides flexibility to architect condition
monitoring hierarchies, and helps manage
complex processes.
Factory
z
AWS IoT Events
AWS Cloud
Monitor asset health and alert when threshold is
breached X times in Y interval
Data origination Ingestion process Monitoring Streaming Actionable
Simplified reference architecture example

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AWS IoT Events for energy & utilities monitoring
Problem
Energy waste and inefficient utilization leads to
malfunctioning products, increased costs, and
diminished power capacity required for
continuous usage.
Solution
AWS IoT Events provides a flexible and
manageable monitoring service to identify and
alert when utilization of energy does not meet
requirements. Together, multiple models can be
arranged to monitor various attributes/products
within a fleet.
Impact
Improve customer experience with better
management of cost-of-use, reduce waste of
energy/utilities, and simplify troubleshooting or
dispatching resources to remote locations by
understanding stateful data metrics.
Products/grid
AWS IoT Events
AWS Cloud
Detect performance or utilization to maintain efficient servicing of
resource consumption prior to exceeding X level
Data generation Ingestion process Monitoring Alert throughput Optimization
Simplified reference architecture example
z

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Industry
AWS IoT Events
AWS Cloud
Proactively maintain a continuous feedback loop for assets
Transportation
Life science/healthcare
Client
Mobile client
Users
Vehicle
AWS IoT Events applied broadly
Problem
Equipment and devices require consistent
monitoring to detect and manage connectivity
or predict maintenance issues. Complex
infrastructure causes latency and delays for
information to be actionable.
Solution
AWS IoT Events provides templates and simple-
to-deploy detector models for multiple use
cases to create a flexible infrastructure that will
scale with fleets, vehicle types, and hardware.
Impact
Reduce factory recalls, maximize capital-
expenditure investments, and improve safety by
continuously monitoring based on a hierarchy of
detector models for optimal performance
management.
Data generation Ingestion filtering Monitoring Data routing Notification/alerts
Simplified reference architecture example
Enterprise

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AWS IoT Events console & detector model
AWS IoT Events console Getting started AWS IoT Events GUI-based detector model creation

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AWS IoT Events launch references
Customers Technology Partners

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“BAI is improving customer connectivity
using IoT Events to enhance end-user
experience”
Alexander Witte
Cloud Architect, BAI Communications

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Transit
communications
Television
and radio
broadcasting
Tower and
fibre
Emergency
services
communications
networks
Venue
connectivity
Transit
authorities
Enterprise
and business
Television
and radio
broadcasters
Mobile network
operators
Public safety
agencies and
government
We deliver
to
What we do at BAI Communications
In a world where connectivity is essential to our daily lives, we design, build, and operate
communications infrastructure—cellular, Wi-Fi, broadcast, radio, and IP networks—connecting
communities around the world.
We operate in Toronto, New York, the UK, Hong Kong, and Australia.

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The challenge of providing a high-quality customer
experience
200,000
5 million
100,000
900+
75
45 miles
Question: How do we measure, alert, and troubleshoot Wi-Fi
connectivity to improve customer experience?

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Raspberry Pi Touchstone sensor inside access point enclosure
Project Touchstone: Measuring network performance by
user simulation
What are the Touchstone steps?

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Solution: Building an architecture with AWS IoT Events
AWS IoT Core
AWS IoT Events
Detector Model 1
AWS IoT
Analytics
Amazon S3
AWS Lambda Amazon EC2
AWS Systems Manager
Touchstone
sensor
AWS Cloud
Management network
HTTP proxy
Amazon SNS
Touchstone remote device manager
Secure AND resizable compute capacity
Time-series Visualization
AWS IoT Events
Detector Model 2
AWS IoT Events station model
Notification output
Transit station
Dataingestion

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AWS IoT Events: Examining multiple detector models for
Wi-Fi status monitoring
Transit station
Touchstone
Sensor A
Touchstone
Sensor B
AWS Cloud
AWS IoT Core
AWS IoT Events network
performance detector model
AWS IoT Events station
health detector model
Sensor state – A
Sensor state – B
Transit station state
Good
Good
Good
Bad
Bad
Critical
Critical
CriticalBad
AWS IoT Analytics
AWS IoT Analytics
aggregates sensor state
data by station
Detector Model 1
Detector Model 2
Dataingestion

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BAI outcomes: Insights gained from AWS IoT Events
implementation
Streaming real-time data metrics
Monitoring station performance and traffic levels Alexa-enabled flashboard to visually display TCONNECT health status

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Next steps:
Wireless AP enclosure
BAI future: Continuing to advance the customer
experience
Goal: To provide a consistent and responsive Wi-Fi experience
for every TCONNECT user

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Thank you!
S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Raghu Pillutla
pillutla@amazon.com
Alexander Witte
alexander.witte@baicanada.com
Imran Rafique
imranraf@amazon.com
Asim Kumar Sasmal
sasasim@amazon.com