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Microsoft Azure-powered
IoT & AI Solution
To Help Farmer
Use Case & Technical Perspective, AI at the Edge / TinyML
Microsoft //DevCon/ Digital Economy Summit 2020

The Ritz Carlton Jakarta

Feb 27, 2020
Andri Yadi
CEO, DycodeX

Microsoft MVP, Azure
Andri Yadi
Co-founder & CEO of DycodeX
Vice Chairman, Indonesia IoT Association
Microsoft MVP, Azure
a (at) dycodex.com | andriyadi.com | github.com/andriyadi
Physicist, Developer, Maker, Community Guy, Entrepreneur
About Me
MicrosoQ Most Valuable Professional (MVP) for 12 years

Code for food & passion for 20 years

Break & make electronic stuUs for 22 years

Trying to change the world through entrepreneurship, 15 years now
”“I have to visit hundreds of cows every day,
just to check if they still move or not”

A caretaker in Cattle Breeding Centre - Ministry of Agriculture
Manages 1400+ cows
”HERD TRACKING
“We often lose counting when a herd of cows
moves from one to another grazing area”

A big-size farm, Indonesia, manages 8000+ cows
BEHAVIOUR TRACKING
“We have no reliable means to track cow’s feeding
behaviour. Non-eating cows are often found dead
after 2-3 days”

A medium-size farm, Subang - Indonesia
Manages 400+ cows
BASE STATION
5-10 km coverage,
to connect devices
with Cloud.
* Can be NB-IoT, Cellular, or
LoRa/LoRaWAN
WEARABLE DEVICE
Device worn by cattle
contains plethora of sensors
BARN SENSORS
Collection of sensors to
monitor environment,
water & food supply,
and more
FARM MANAGER /
OWNER / INVESTOR
Monitor the farm and manage
operation comfortably from
anywhere in the world
DRONE
Provide surveillance
and help herding.
VIRTUAL FENCE
Contain and move
cattle without physical
posts and wires.
CLOUD
Where the heavy-
lifting happens.
CARETAKER
One farmer/
caretaker can easily
handle hundreds of
cattle, and vast
grazing area
SMART CAMERA
Monitor behaviour of 5
- 10 cattle, count herd,
and more using
AI-powered Machine
Vision.
The Solution
* “Ternak” in SMARTernak means “cattle” in Bahasa Indonesia
AIoT-powered Livestock-Farming Assistance
Platform
6
That’s exactly

On-farm SmaE Camera:

Monitor activity of 5 - 10 cattle -
focus on group activity
Count herd & movement
CaGle-wearable device:

Precisely monitor each
cacle for:

Location: latitude, longitude,
movement speed, direction
Body temperature
Ambient temperature & humidity
Ambient light & sound
Movement: linear acceleration,
angular velocity, direction
Device removal status
Battery voltage & capacity
Monitoring & Insights
Barn Sensors:

Monitor ambient temperature,
humidity, and air quality in barn
Monitor food & water supply
Monitor caGle where-about & well-being

Provide insights - powered by AI - to help
increasing yield and reducing loss
Low Power
Wide Area

Network 

(LPWA)
High Level Architecture
Gateways /

Base Stations
Things
Internet
Apps
Ingestion
(Network Server)
Infrastructure
Logics
API
Cloud User
Internet
Drone*
SmaE Cam
Wearable
Water & Food
Monitoring
Ambient
Environment
* In development
Cattle-wearable Device
Dual IoT Connectivity
Short Range: Bluetooth v5, BLE
Long Range: LoRa/LoRaWAN or NB-IoT,
for 5-10km coverage area
Powerhouse
Ultra low power Microcontroller
with on-device Machine Learning capability
Smart Energy
Battery Gauge
Solar Energy Harvesting
Smart Switching Between
Main & Backup Battery
Fast Charging from USB Type-C
Firmware-optimised
power consumption
Packed with Sensors
GPS / GNSS
Accelerometer, Gyroscope, Compass
Body Temperature
Ambient Temperature & Humidity
Barometric Pressure
Ambient Light
MEMS Microphone
Device Removal Detector
Actuators
Audio Alert via Buzzer
Color LED
Enclosure
Waterproof &
submersible (IP67)
Hardware is 100% designed in-house, mass-
produced in Indonesia, by 100% IndonesianBut SMARTernak is about platform.
It’s open to 3rd party devices.
How it’s worn
Let’s dive into a feature: On-device Activity Prediction
Demo Video: http://bit.ly/smrtrnk-ai-3
Built-in
IMU Sensor
Possible to transmit
reliably over 

LPWA
Predicted activity

(standing, lying-down, feeding, and more)
App
Raw data

5D 1B 16
56 01 41 

(1080 Bytes)
Processed data

0A 0B 01
(3 Bytes)
{
“cattle_id”: 2,
“act”, “standing”,‹


}
LPWA = Low Power Wide Area Network
Payload length: ~200 - 1600 bytes
Learn & predict cattle activities based on sensor data with
the help of on-device Machine Learning
AI at The Edge
Deep Neural Network

(Run on Microcontroller in device)
Standing
Why the hassle?
walking
walking
walking
Type Komodo
Animal activity recognition

No need to visually observe the animal activity.
Focus the acention to troubled animals
Activity stats:

Activity count and duration statistic during cejain
timespan

Activity duration and switching. Can be used for
determining symptoms of possible health issues. 

AleE when animal has stopped moving, not feeding,
not enough activity, and more
It’s all about tailoring Activity Insights & Recommendation
Achieving AI at The Edge
And how Azure helps
Azure Machine Learning Pipeline
TensorFlow model Zle
Compress
TFLite
Flat

Bu[er
ConveE
C Byte
ArrayIntegrate
into MCU
Firmware
TinyML Pipeline
Custom 

Logics
ML Model
Microcontroller (MCU) Firmware
TensorFlow Lite

for Microcontroller
Machine Learning
ClassiZcation 

What’s happening right now?

Anomaly Detection

Is it “normal”?

Forecasting 

What will happen in the future?
Some ML problems
For those problems,
ML Inference is possible on
ultra-low power, low cost,
tiny Microcontroller
Cattle Activity Recognition
GPS & Compass
Activity &
Performance Insights
Long Range
Low Power IoT
Connectivity
Notify Cattle
Health-related
Issues
On-device
Artificial
Intelligence
All-1/2-year Battery Life
and some more, with energy harvesting from solar
Sense Surrounding Environment
Virtual Geofencing
Out of Area Alert, Herd Counting
& Grazing Insights
Smart Energy
with Backup Battery &
Energy Harvesting
with 2G Fallback
Device
Removal
Alert
NFC-A
Bluetooth 5
CPU
64 MHz
Cortex-M4F
1 MB
Flash
Crypto
DC-DC
Buck
Converter
AES
Co-processor
RAM
256kB
https://smarternak.com
3 variants for all farm types
Health
Tracking
Ultimate
© 2019. DycodeX. https://dycodex.com
Sits firmly on cow’s neck
Wearable
Recognition powered by TinyML running on MCU
Microso] MVP:
Find MVP or Join the elite group: hcps://mvp.microsoQ.com/

Azure:
Azure Machine Learning: hcps://azure.microsoQ.com/en-in/services/
machine-learning-service/

DycodeX:
SMARTernak: hcps://smajernak.com 

ESPectro32 dev board: hcps://shop.makestro.com/product/espectro32-v2/ 

Other IoT + AI products & solutions: hcps://dycodex.com 

TinyML:
TensorFlow Lite for Microcontrollers: hcps://www.tensomlow.org/lite/
microcontrollers

Contact me:
andri@dycodex.com 

hcp://github.com/andriyadi | hGps://slideshare.net/andri_yadi/
Call to Action
MVP Booth
NOTES:
- Size : 300 x 200 cm
- Power Electricity : 6 ampere / 1300 watt
- TV 43 Inch : 2 units with HDMI connectors
- Power port : 2 Spots @ 4 ports
- Internet : 2mbps provided per booth
- ID Card : 4 pcs
- Others : Storage, Table, 4 chairs
- Collaterals : Flyers, swags, any small
materials are okay. Stand-up
banners are not allowed
Check out some
cool demos at
our booth!
PT. DycodeX Teknologi Nusantara
Today, we're pioneering and leading in developing end-to-end home-
grown A"i$cial Intelligence (AI) & Internet of Things (IoT)-based
products & solutions in Indonesia.

Only a few of staEups in the country capable of doing both AI & IoT,
in-house!
As seen on
My Company
Our vision is to solve big problems with technology.
AI + IoT enabler
Real World Products & Solutions
Home-grown AI & IoT-powered devices & platforms
EnvironmentAgricultureAsset tracking Energy Design House
AITrash
Smart Trash Management
PowtraX
Electricity metering
Smarterbike:
Bike Fleet Management
(e.g: bike sharing)
DytraX:
Asset Tracking Platform
IoT Prototyping
Platform for
Education, Makers
Custom hardware
design:
already helped 15
companies/startups
End-to-end AI + IoT
development:
firmware, cloud, AI,
web & mobile app
Industrial IoT
Machinery Health
Sensor
Alora
Industrial Environmental
Sensing
SMARTernak
Livestock-farming
assistance
DycodeX IoT Prototyping Platform - for Education & Makers
IoT Prototyping Pladorm
Optimized for learning STEM, coding
& electronics, also for fast
prototyping

Hardware:
ESPectro: A low cost ESP8266-based
development board having capable
Microcontroller, built-in WiFi connectivity 

ESPectro32: A ESP32-based development
board having highly capable, low-power
dual-core Microcontroller, with built-in
WiFi & Bluetooth connectivity

Extensible with Backpacks: NB-IoT/
Cellular, LoRa, Sensor Kits, Motor Driver,
and more

SoQware:
Arduino SoQware-compatible, enriched
by easy-to-use libraries

Learn to code with:
Visual drag-and-drop blocks*

IoT Cloud: to easily connect IoT devices
NB-IoT + GPS/
GNSS Kit
LoRa/LoRaWAN
+ GNSS Kit
Sensors & Actuators
Kit (20+ Peripherals)
3G + GNSS +
Sensors
* in development
ESPectro32
All electronic boards are 100% designed & assembled in-house
Backpacks
ESPectro
AI + IoT enabler
Keep in touch
hi (at) dycodex.com | https://dycodex.com
Bandung, Indonesia

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Microsoft Azure-powered IoT & AI Solution To Help Farmer

  • 1.
  • 2. Microsoft Azure-powered IoT & AI Solution To Help Farmer Use Case & Technical Perspective, AI at the Edge / TinyML Microsoft //DevCon/ Digital Economy Summit 2020 The Ritz Carlton Jakarta Feb 27, 2020 Andri Yadi CEO, DycodeX Microsoft MVP, Azure
  • 3. Andri Yadi Co-founder & CEO of DycodeX Vice Chairman, Indonesia IoT Association Microsoft MVP, Azure a (at) dycodex.com | andriyadi.com | github.com/andriyadi Physicist, Developer, Maker, Community Guy, Entrepreneur About Me MicrosoQ Most Valuable Professional (MVP) for 12 years Code for food & passion for 20 years Break & make electronic stuUs for 22 years Trying to change the world through entrepreneurship, 15 years now
  • 4. ”“I have to visit hundreds of cows every day, just to check if they still move or not” A caretaker in Cattle Breeding Centre - Ministry of Agriculture Manages 1400+ cows ”HERD TRACKING “We often lose counting when a herd of cows moves from one to another grazing area” A big-size farm, Indonesia, manages 8000+ cows BEHAVIOUR TRACKING “We have no reliable means to track cow’s feeding behaviour. Non-eating cows are often found dead after 2-3 days” A medium-size farm, Subang - Indonesia Manages 400+ cows
  • 5. BASE STATION 5-10 km coverage, to connect devices with Cloud. * Can be NB-IoT, Cellular, or LoRa/LoRaWAN WEARABLE DEVICE Device worn by cattle contains plethora of sensors BARN SENSORS Collection of sensors to monitor environment, water & food supply, and more FARM MANAGER / OWNER / INVESTOR Monitor the farm and manage operation comfortably from anywhere in the world DRONE Provide surveillance and help herding. VIRTUAL FENCE Contain and move cattle without physical posts and wires. CLOUD Where the heavy- lifting happens. CARETAKER One farmer/ caretaker can easily handle hundreds of cattle, and vast grazing area SMART CAMERA Monitor behaviour of 5 - 10 cattle, count herd, and more using AI-powered Machine Vision. The Solution
  • 6. * “Ternak” in SMARTernak means “cattle” in Bahasa Indonesia AIoT-powered Livestock-Farming Assistance Platform 6 That’s exactly

  • 7. On-farm SmaE Camera: Monitor activity of 5 - 10 cattle - focus on group activity Count herd & movement CaGle-wearable device: Precisely monitor each cacle for: Location: latitude, longitude, movement speed, direction Body temperature Ambient temperature & humidity Ambient light & sound Movement: linear acceleration, angular velocity, direction Device removal status Battery voltage & capacity Monitoring & Insights Barn Sensors: Monitor ambient temperature, humidity, and air quality in barn Monitor food & water supply Monitor caGle where-about & well-being Provide insights - powered by AI - to help increasing yield and reducing loss
  • 8. Low Power Wide Area Network (LPWA) High Level Architecture Gateways / Base Stations Things Internet Apps Ingestion (Network Server) Infrastructure Logics API Cloud User Internet Drone* SmaE Cam Wearable Water & Food Monitoring Ambient Environment * In development
  • 9. Cattle-wearable Device Dual IoT Connectivity Short Range: Bluetooth v5, BLE Long Range: LoRa/LoRaWAN or NB-IoT, for 5-10km coverage area Powerhouse Ultra low power Microcontroller with on-device Machine Learning capability Smart Energy Battery Gauge Solar Energy Harvesting Smart Switching Between Main & Backup Battery Fast Charging from USB Type-C Firmware-optimised power consumption Packed with Sensors GPS / GNSS Accelerometer, Gyroscope, Compass Body Temperature Ambient Temperature & Humidity Barometric Pressure Ambient Light MEMS Microphone Device Removal Detector Actuators Audio Alert via Buzzer Color LED Enclosure Waterproof & submersible (IP67) Hardware is 100% designed in-house, mass- produced in Indonesia, by 100% IndonesianBut SMARTernak is about platform. It’s open to 3rd party devices.
  • 11. Let’s dive into a feature: On-device Activity Prediction Demo Video: http://bit.ly/smrtrnk-ai-3
  • 12. Built-in IMU Sensor Possible to transmit reliably over LPWA Predicted activity (standing, lying-down, feeding, and more) App Raw data 5D 1B 16 56 01 41 
 (1080 Bytes) Processed data 0A 0B 01 (3 Bytes) { “cattle_id”: 2, “act”, “standing”,‹ 
 } LPWA = Low Power Wide Area Network Payload length: ~200 - 1600 bytes Learn & predict cattle activities based on sensor data with the help of on-device Machine Learning AI at The Edge Deep Neural Network (Run on Microcontroller in device) Standing
  • 13. Why the hassle? walking walking walking Type Komodo Animal activity recognition No need to visually observe the animal activity. Focus the acention to troubled animals Activity stats: Activity count and duration statistic during cejain timespan Activity duration and switching. Can be used for determining symptoms of possible health issues. AleE when animal has stopped moving, not feeding, not enough activity, and more It’s all about tailoring Activity Insights & Recommendation
  • 14. Achieving AI at The Edge And how Azure helps Azure Machine Learning Pipeline TensorFlow model Zle Compress TFLite Flat Bu[er ConveE C Byte ArrayIntegrate into MCU Firmware TinyML Pipeline Custom Logics ML Model Microcontroller (MCU) Firmware TensorFlow Lite for Microcontroller
  • 15. Machine Learning ClassiZcation What’s happening right now? Anomaly Detection Is it “normal”? Forecasting What will happen in the future? Some ML problems For those problems, ML Inference is possible on ultra-low power, low cost, tiny Microcontroller
  • 16. Cattle Activity Recognition GPS & Compass Activity & Performance Insights Long Range Low Power IoT Connectivity Notify Cattle Health-related Issues On-device Artificial Intelligence All-1/2-year Battery Life and some more, with energy harvesting from solar Sense Surrounding Environment Virtual Geofencing Out of Area Alert, Herd Counting & Grazing Insights Smart Energy with Backup Battery & Energy Harvesting with 2G Fallback Device Removal Alert NFC-A Bluetooth 5 CPU 64 MHz Cortex-M4F 1 MB Flash Crypto DC-DC Buck Converter AES Co-processor RAM 256kB https://smarternak.com 3 variants for all farm types Health Tracking Ultimate © 2019. DycodeX. https://dycodex.com Sits firmly on cow’s neck Wearable Recognition powered by TinyML running on MCU
  • 17. Microso] MVP: Find MVP or Join the elite group: hcps://mvp.microsoQ.com/ Azure: Azure Machine Learning: hcps://azure.microsoQ.com/en-in/services/ machine-learning-service/ DycodeX: SMARTernak: hcps://smajernak.com ESPectro32 dev board: hcps://shop.makestro.com/product/espectro32-v2/ Other IoT + AI products & solutions: hcps://dycodex.com TinyML: TensorFlow Lite for Microcontrollers: hcps://www.tensomlow.org/lite/ microcontrollers Contact me: andri@dycodex.com hcp://github.com/andriyadi | hGps://slideshare.net/andri_yadi/ Call to Action
  • 18. MVP Booth NOTES: - Size : 300 x 200 cm - Power Electricity : 6 ampere / 1300 watt - TV 43 Inch : 2 units with HDMI connectors - Power port : 2 Spots @ 4 ports - Internet : 2mbps provided per booth - ID Card : 4 pcs - Others : Storage, Table, 4 chairs - Collaterals : Flyers, swags, any small materials are okay. Stand-up banners are not allowed Check out some cool demos at our booth!
  • 19. PT. DycodeX Teknologi Nusantara Today, we're pioneering and leading in developing end-to-end home- grown A"i$cial Intelligence (AI) & Internet of Things (IoT)-based products & solutions in Indonesia. Only a few of staEups in the country capable of doing both AI & IoT, in-house! As seen on My Company Our vision is to solve big problems with technology. AI + IoT enabler
  • 20. Real World Products & Solutions Home-grown AI & IoT-powered devices & platforms EnvironmentAgricultureAsset tracking Energy Design House AITrash Smart Trash Management PowtraX Electricity metering Smarterbike: Bike Fleet Management (e.g: bike sharing) DytraX: Asset Tracking Platform IoT Prototyping Platform for Education, Makers Custom hardware design: already helped 15 companies/startups End-to-end AI + IoT development: firmware, cloud, AI, web & mobile app Industrial IoT Machinery Health Sensor Alora Industrial Environmental Sensing SMARTernak Livestock-farming assistance
  • 21. DycodeX IoT Prototyping Platform - for Education & Makers IoT Prototyping Pladorm Optimized for learning STEM, coding & electronics, also for fast prototyping Hardware: ESPectro: A low cost ESP8266-based development board having capable Microcontroller, built-in WiFi connectivity ESPectro32: A ESP32-based development board having highly capable, low-power dual-core Microcontroller, with built-in WiFi & Bluetooth connectivity Extensible with Backpacks: NB-IoT/ Cellular, LoRa, Sensor Kits, Motor Driver, and more SoQware: Arduino SoQware-compatible, enriched by easy-to-use libraries Learn to code with: Visual drag-and-drop blocks* IoT Cloud: to easily connect IoT devices NB-IoT + GPS/ GNSS Kit LoRa/LoRaWAN + GNSS Kit Sensors & Actuators Kit (20+ Peripherals) 3G + GNSS + Sensors * in development ESPectro32 All electronic boards are 100% designed & assembled in-house Backpacks ESPectro
  • 22. AI + IoT enabler Keep in touch hi (at) dycodex.com | https://dycodex.com Bandung, Indonesia