Hyderabad Trailblazin’ - Building Connected Solutions

Session on Building Connected Solutions presented at Hyderabad Trailblazin'

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Hyderabad
Trailblazin’
AI+Data+Trust+CRM
#HYDTRAILBLAZIN

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THANK YOU TO OUR TRAILBLAZIN’ PARTNERS
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3. Tarandeep
Singh
Software Engineer,
Salesforce

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Get Started with Building Connected
Solutions
Salesforce + Mulesoft + Heroku + IoT + AI
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5. Dr. Tarandeep SinghMrs. Preeti Sharma
Personas
Cardiologist Doctor at Apollo
Hospital
A Patient with CHD (Congenital
Heart Disease)

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Demo
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8. Salesforce Implementation
●Implemented Salesforce Health Cloud for
doctor
●Custom Reports & Dashboards
●Lifeblood AppExchange
●Security & Setup Encryption for sensitive
data like Aadhar Card/SSN
●Exposed Rest APIs for integration with
external applications
●Platform Events (Pub-Sub Model)
●Next Best Actions for doctors
●Custom Lightning components

10. Salesforce Experience Cloud Implementation
●Salesforce Customer community
●Data shared with Salesforce instance
●Lifeblood - Blood donation app
●Chatter & groups
●Monitoring IoT devices data
●Scheduling appointments
●Knowledge articles

11. Android App Implementation
●Uses Salesforce SDK
●Protocol developed by Apple
●Uses Bluetooth Low Energy (BLE) to
connect to nearby iBeacons
●Uses Salesforce Rest APIs to publish
Platform Events (Pub - Sub Model)
●Salesforce listen to events to performs the
relevant actions using lightning components

13. IoT Middleware Implementation
●Built using MuleSoft for APIs and business
logic integration with Salesforce
●Utilizes MuleSoft Anypoint Platform for
integration and API management
●Exposes APIs for IoT devices to push
real-time data to the database
●Includes data filtering mechanisms within
MuleSoft flows
●Uses Salesforce Connector

15. Healthcare IoT Implementation
●Healthcare IoT devices for real time
monitoring patients
●Developed on Arduino IDE with C/C++
programming language
●Used MAX30102 Pulse Oximeter sensors for
monitoring oxygen level and Pulse sensors
for monitoring heart rate.
●Sensors are connected to a microcontroller
(Arduino UNO based on ATmega328P)

17. AI Implementation
●Web API based application deployed on Heroku
●Utilizes data from Pulse Heart Rate sensors to
predict potential heart attacks.
●Employs Python along with AI libraries for reading,
parsing, training, and predicting data.
●Integrated with Salesforce to analyze patient data
stored within Salesforce for heart problem
predictions.
●Uses the AdaBoost Classification algorithm on the
training data set for classification.
●Heroku provides a scalable, reliable, and fully
managed platform for deploying this AI application,
ensuring seamless integration and optimal
performance.

20. Resources

1.Trailmix - https://sforce.co/3KjoLE4
2.AI Associate Certification - https://trailhead.salesforce.com/en/credentials/aiassociate
3.Mulesoft Certification - https://trailhead.salesforce.com/en/credentials/mulesoftoverview/
4.Salesforce Health Cloud - salesforce.com/products/health-cloud/overview/
5.Pulse sensors for monitoring heart rate- https://pulsesensor.com/
6.MAX30102 Pulse Oximeter sensors -
maximintegrated.com/en/products/interface/sensor-interface/MAX30102.html
7.Estimote ibeacons - estimote.com
8.AI dataset source - archive.ics.uci.edu/ml/machine-learning-databases/heart-disease/
9.Lifeblood AppExchange -
appexchange.salesforce.com/appxListingDetail?listingId=a0N3A00000FMiQuUAL
10.Heart Rate Prediction : https://github.com/Tdssaini/heart_disease_ai_prediction

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Q & A
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Session Question
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Sponsor Question
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Blue5Green is specialized in ?
●Azure Accelerators
●SAP Accelerators
●AI Power Accelerators
●Power Accelerators

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THANK YOU!
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