Industrial Automation, AI Integration & Capstone - Become an Industry 4.0 Engineer in 45 Days
Program PLCs, design SCADA dashboards, deploy Edge AI on ESP32-S3, and build a digital-twin capstone that an industry panel will actually evaluate. The placement-ready finale of the Embedron program at Elysium Embedded School.
70% hands-on labs across 30+ professional experiments
Capstone judged by an external 3-member industry panel
4 industry tracks: Agriculture • Manufacturing • Defense • Transport
DGCA-aware drone safety + IEC 62443 OT cybersecurity baked in
Direct pathway to roles at Bosch, L&T, Tata Elxsi, BEL, Ola Electric, Ather and others
Design Intelligent Machines for the Future of Automation & Robotics
Drone Technology & Mechatronics Professional Training
- Course Overview
- Course Objectives
- Learning Outcomes
- Who Should Enroll
- Course Features
- Industry & Job Connect
Embedron Module 4 is the final and most demanding phase of the Embedron program. It is where everything you built across electronics, embedded firmware, IoT, robotics and drones converges into a single, defensible Industry 4.0 portfolio piece. You do not write essays about Industry 4.0 here. You build it.
Across 45 deliberately sequenced days, you will program a real PLC using the IEC 61131-3 standard, design operator-grade SCADA and HMI screens that comply with ISA-101, bridge plant-floor data via OPC-UA and Modbus, train and quantise neural networks that run inside microcontrollers, build a queryable digital twin in the cloud, and tie it all together with a Flutter mobile app for the operator on the shop floor.
The module is intentionally aligned to the way modern Indian factories, agritech polyhouses, defense forward posts and EV fleets actually operate. Every lab references a real deployment pattern used by companies such as Tata Motors, Bajaj Auto, ITC, Stellapps, Ola Electric and Ather. You will not be solving toy problems - you will be replicating, in miniature, the systems that power crore-scale operations.
Why This Module Matters
Two trends collide in this module. First, India’s manufacturing economy is being reshaped by the PLI scheme, the Semicon India Mission, and the push toward defence indigenisation - and every one of those programmes needs engineers fluent in PLCs, SCADA, OPC-UA and edge intelligence. Second, the cost of running AI has crashed to a point where neural networks routinely fit inside ₹250 microcontrollers, unlocking a generation of products that did not exist five years ago.
Module 4 is positioned squarely at this collision. By the time you walk into your demo day, you will not only understand the buzzwords - you will have shipped a working artefact for each one of them.
The Embedron Promise
A working Industry 4.0 capstone, evaluated and signed off by an external industry panel.
A GitHub portfolio with hardware schematics, firmware, cloud DTDL models, mobile app and demo video.
Two industry-aligned certifications from Elysium Embedded School plus a roadmap to AZ-220, AWS IoT Specialty and ISA CAP.
A pre-built placement dossier delivered to Embedron’s hiring-partner network across India.
Where Embedron Module 4 Fits In Your Career
| Stage | What You Should Know | What Module 4 Adds |
|---|---|---|
| After Module 1 | Sensors, MCU firmware, PCB basics | Foundation only - not yet Industry 4.0 |
| After Module 2 | Wi-Fi, MQTT, LoRa, mobile app integration | Internship-eligible IoT developer |
| After Module 3 | Robotics, ROS 2, drone autonomy | Field-engineer ready in robotics or drones |
| After Module 4 | PLCs + SCADA + OPC-UA + Edge AI + Digital Twin + Capstone | Placement-ready Industry 4.0 engineer |
Real-World Use Cases You Will Build
- A greenhouse command centre that uses PLC valve control and edge-AI plant-stress detection (Agriculture track)
- A conveyor predictive-maintenance system with vibration anomaly detection and a digital twin (Manufacturing track)
- A hardened sentry node with on-device acoustic classification and air-gapped twin reporting (Defense track)
- An EV battery telemetry stack with CAN-bus BMS, driver-behavior AI and a fleet twin (Transport track)
By the end of Module 4, you will be able to design, build, secure and demonstrate a complete Industry 4.0 system end-to-end. Each objective below maps to verifiable deliverables in the lab manual and the capstone rubric.
Outcomes are measurable. Each is mapped to a lab, a capstone deliverable or a panel-evaluated demo so that progress can be evidenced - not just claimed.
Technical Outcomes
- Build a three-wire motor starter circuit in Ladder Logic with seal-in, stop and overload, and explain its scan-cycle behaviour.
- Implement a tank-level PID controller in Structured Text using a Function Block library.
- Scale a 4–20 mA pressure transducer reading into engineering units and surface it on an HMI.
- Bridge a PLC to MQTT via an OPC-UA client running on Raspberry Pi.
- Train a 3-class IMU motion classifier on Edge Impulse and deploy it to ESP32-S3 with sub-5 ms inference.
- Run a keyword spotter on a PDM microphone using MFCC features and a quantised CNN.
- Compute FFT, RMS and kurtosis features on motor vibration data and detect anomalies with an autoencoder.
- Author a DTDL conveyor model, push live telemetry to Azure Digital Twins, and round-trip a setSpeed command.
Professional Outcomes
- Write production-grade firmware with error handling, watchdogs and signed OTA pipelines.
- Produce an 8-page engineering report with architecture diagrams, BOM and risk register.
- Deliver a 12-minute capstone pitch to an external industry panel with confident Q&A.
- Maintain a portfolio-grade GitHub repository with structured README, schematics and demo video.
Industry Readiness Outcomes
- Articulate the differences between RAMI 4.0, IIRA and ISO 23247 reference models.
- Defend security choices against IEC 62443 zoning principles and CERT-In’s OT directives.
- Map any of your Embedron projects onto a deployable Indian factory, farm, base or vehicle pattern.
Module 4 is the placement-readiness phase of Embedron. It is purpose-built for learners who have completed Modules 1–3 (or can demonstrate equivalent project experience) and want to compress the gap between college and the Industry 4.0 job market.
Prerequisites
- Completion of Embedron Modules 1, 2 and 3, or demonstrable equivalent in embedded firmware, IoT and robotics.
- Comfort with C/C++ on Arduino/ESP32 and Python on Linux/Raspberry Pi.
- Working knowledge of MQTT, basic networking and command-line Linux.
- Willingness to commit 1.5 hours daily for 45 days plus weekend project time during the capstone.
Who This Module Is Not For
- Absolute beginners with no embedded background - start with Module 1 instead.
- Learners looking for a purely theory-based or certification-only course.
- Anyone unwilling to demo their own work to an external panel on the final day.
Ideal Learner Profiles
| Profile | Why This Module Is For You |
|---|---|
| 3rd / 4th Year Engineering Students (ECE, EEE, CSE, Mech, Mechatronics, IT, AI&DS) | Convert academic theory into a placement-grade portfolio in a single semester. |
| Recent Graduates Without Industry Exposure | Acquire the exact toolchain - PLCs, OPC-UA, TinyML, Digital Twins - that recruiters list as ‘must-have’. |
| Working Embedded Engineers (0–2 years) | Reskill into higher-paying Industry 4.0, Edge AI and digital-twin roles. |
| Polytechnic Diploma Holders With Hands-On Aptitude | Bridge into engineering-grade roles by demonstrating capstone-level proof-of-work. |
| Career Switchers From IT / Software Roles | Add a hardware-and-controls dimension that opens the OT side of the job market. |
| Aspiring Deep-Tech Founders | Validate a sellable Industry 4.0 product idea with a working PLC + AI + twin prototype. |
| Faculty And Trainers | Adopt a turnkey, externally-evaluated capstone framework for your own institutions. |
Every feature below is a deliberate design choice tested across multiple cohorts. They are not marketing checkboxes - each one maps to a measurable outcome on your transcript or in your portfolio.
Hands-On Engineering
- 70:30 practical-to-theory ratio across all 45 days.
- 20+ professionally documented lab experiments, each in the same 12-section industry format.
- Real PLCs, real ESP32-S3 boards, real Raspberry Pi gateways, real motor benches - not just simulators.
Capstone-First Design
- Industry 4.0 capstone evaluated by an external 3-member panel from manufacturing, EV or defense.
- Rubric weighted at 40% of the module grade - the capstone is the assessment, not an afterthought.
- Track-specific capstone variants (Agriculture, Manufacturing, Defense, Transport) so your portfolio fits a specific recruiter.
Certification
- Embedron Industry 4.0 Practitioner certificate on successful completion.
- Embedron Distinction Award for cohort top performers (≥ 85% overall and ≥ 85% capstone).
- Stackable preparation for AZ-220, AWS IoT Specialty, ISA CAP and Edge Impulse Certified Developer.
Career Acceleration
- Internship-readiness dossier auto-generated for all qualified learners.
- Mock interview rounds and embedded-systems aptitude practice on Days 178-179.
- LinkedIn-portfolio coaching, GitHub-hygiene review, and resume rewrite during career week.
- Demo-day panel access - your work is seen by people who actually hire.
Mentorship & Community
- 1 capstone mentor for every 6 learners - not 1 for every 60.
- One industry guest per module, drawn from active practitioners in Indian Industry 4.0.
- Lifetime alumni access to the Embedron Slack and recurring office hours.
Resources & LMS
- Lifetime access to the Embedron LMS with recorded lab playthroughs.
- Downloadable lab workbooks, schematics, DTDL model templates and OPC-UA reference servers.
- Cloud trial credits for Azure IoT Hub and Azure Digital Twins on the free tier.
Safety & Compliance
- DGCA-aligned drone safety hand-off from Module 3 carried forward into the capstone.
- Mandatory ESD discipline, lockout-tagout practice on motor benches and isolation on mains-adjacent labs.
- CERT-In aligned OT security postures applied to every cloud-connected build.
Module 4 is engineered around the actual hiring patterns of Indian Industry 4.0 employers. Below is a clear-eyed view of which roles open up, what they pay, who hires, and what skills they look for.
Market Demand Snapshot
- Indian Industry 4.0 spending across manufacturing, EV and infrastructure is projected to grow at a double-digit CAGR through 2030.
- Edge-AI and TinyML roles are forecast to be among the fastest-growing engineering specialisations in India.
- Defence indigenisation (DRDO, BEL, BDL, iDEX startups) is creating sustained demand for ruggedised embedded engineers.
- The EV transition is producing entirely new role families - BMS engineer, EV telematics engineer, charging-infra controls engineer.
Job Roles You Become Eligible For
- Industrial Automation Engineer
- PLC / SCADA Engineer
- Edge AI / TinyML Engineer
- Predictive Maintenance Engineer
- Digital Twin Developer
- Industry 4.0 Solutions Architect (junior)
- IoT Firmware Engineer
- OT Cybersecurity Analyst (junior)
- EV Telematics / BMS Engineer
- Smart-Manufacturing Application Engineer
- Embedded R&D Engineer (Industrial)
- Agritech IoT Engineer
- Defense Embedded Engineer
- Field Application Engineer (Automation)
- Technical Pre-Sales Engineer (Industrial IoT)
Indicative Salary Bands (India, Entry-Level)
| Role | Indicative CTC (₹ LPA) | Typical Employers |
|---|---|---|
| PLC / SCADA Engineer | 4 - 8 | L&T, Siemens, ABB, Rockwell partners |
| Industrial Automation Engineer | 5 - 9 | Tata Motors, Bajaj Auto, Maruti Suzuki, Bosch |
| Edge AI / TinyML Engineer | 8 - 14 | Tata Elxsi, Wipro PARI, deep-tech startups |
| Digital Twin Developer | 7 - 13 | TCS, Infosys, Capgemini, Cognizant |
| BMS / EV Telematics Engineer | 6 - 12 | Ola Electric, Ather, TVS, Mahindra Electric |
| IoT Firmware Engineer | 5 - 10 | Stellapps, CropIn, Fasal, smart-city integrators |
| Defense Embedded Engineer | 6 - 12 | BEL, BDL, HAL, Tata Advanced Systems, L&T Defence |
| Predictive Maintenance Engineer | 6 - 12 | Industrial AI startups, EMS companies |
Hiring Industries
- Discrete and process manufacturing (auto, FMCG, pharma, steel, cement)
- Energy and utilities (grid, renewables, oil & gas, water)
- EV and mobility (OEMs, charging infrastructure, fleet operators)
- Defense and aerospace (DRDO labs, defense PSUs, iDEX startups)
- Agritech and food supply chain (polyhouse, irrigation, cold chain)
- Smart cities and infrastructure (lighting, water, waste, parking)
- Industrial IoT and edge-AI product companies
- System integrators and EMS (electronics manufacturing services)
Global Pathways
- Industry 4.0 engineering roles in Germany, Singapore and the UAE remain heavily under-supplied.
- Edge-AI specialisations open up direct paths to roles at firms with global R&D footprints.
- ISA CAP, AZ-220, AWS IoT Specialty and Edge Impulse Certified Developer signal credibility to global recruiters.
Career Pathway
Embedron Module 4 sits at a specific point on the learning curve. The map below shows where you arrive, where you can go in 2 years, and where you can be in 5-7 years if you commit to the trajectory.
Three-Stage Roadmap
| Stage | Timeline | Typical Roles | Capabilities |
|---|---|---|---|
| Beginner - Industry-Ready | Now (post-M4) | Jr Automation Engineer • IoT Firmware Engineer • BMS Engineer | PLC programming, SCADA, MQTT, edge AI prototypes, capstone portfolio |
| Intermediate - Specialist | 1-3 years out | Edge AI Engineer • Digital Twin Developer • Predictive Maintenance Engineer | Production firmware, OPC-UA at scale, model deployment pipelines, IEC 62443 |
| Advanced - Architect / Founder | 3-7 years out | Industry 4.0 Solutions Architect • OT Security Lead • Deep-Tech Founder | Reference architectures, multi-site rollouts, IP creation, technical leadership |
Vertical vs Horizontal Moves
- Vertical: Jr Automation Engineer → Automation Lead → Plant Digitalisation Lead → CTO of a smart factory.
- Horizontal: Embedded firmware engineer → edge AI engineer → MLOps for edge → AI infrastructure roles.
- Domain hop: Manufacturing → EV controls → defense edge AI → aerospace mission systems.
Founder Pathway
- Module 4 capstone has been the seed of multiple student-founded Industry 4.0 startups.
- DPIIT, MeitY TIDE 2.0 and Startup India schemes actively fund hardware + AI deep-tech ventures.
- iDEX (Defence Innovation) and Atal Innovation Mission grants are available for shippable prototypes.
Future Learning Roadmap
Module 4 is an inflection point, not an endpoint. Below is the curated next-step ladder we recommend for learners aiming at top-quartile Industry 4.0 careers.
Immediate Stack (0-6 months after Module 4)
- Microsoft AZ-220 Azure IoT Developer Specialty
- Edge Impulse Certified Developer
- AWS Certified Cloud Practitioner → AWS IoT Specialty
- DGCA Remote Pilot Certificate (for drone-track learners)
- ISA Certified Automation Professional (CAP) preparation
Emerging Technologies (12-24 months)
- Matter / Thread interoperability stacks for cross-vendor IoT
- 5G RedCap and NTN (non-terrestrial networks) for industrial IoT
- Asset Administration Shell (AAS) - the Industry 4.0 self-description standard
- Post-Quantum Cryptography rollouts for OT systems
- On-device LLMs and agentic edge AI for operator co-pilots
- UWB (DW3000) for centimetre-grade indoor positioning
- DDS over TSN for deterministic real-time robotics communication
- Neuromorphic computing for ultra-low-power inference
India-Specific Strategic Themes
- Semicon India Mission - design skills for the upcoming fab ecosystem
- DGCA Drone Rules 2.0 - BVLOS operations and commercial drone services
- Smart Cities 2.0 - water, waste, lighting and transit IoT
- India AI Mission - sovereign foundation-model APIs integrating with edge devices
- ONDC + UPI + IoT payment flows (EV charging, smart kiosks, agritech)
Higher-Education Routes
- M.Tech in Embedded Systems / VLSI / Robotics from IITs, NITs, IIITs
- Specialised PG programs in Industry 4.0 from IISc and TalentSprint partnerships
- MS abroad in Embedded Systems / Robotics - the capstone strengthens your SoP materially
- Research routes via DST / DRDO fellowships and CSIR internships
Detailed Syllabus (Module 4 • Days 136-180)
Each week below is published with topics, labs and outcomes.
Week 1 - Industrial Automation Foundations & PLC Programming (Days 136-142)
You start where every modern factory starts: the controller. This week’s focus is the IEC 61131-3 standard, the PLC scan cycle, and the canonical control patterns that every plant floor in India relies on.
Topics Covered
- Industry 4.0 overview and the five-layer automation pyramid
- PLC architecture: CPU, I/O modules, power supply, scan cycle
- Ladder Logic fundamentals, timers, counters, comparators, math instructions
- Structured Text and Function Block Diagram
- Analog I/O, 4–20 mA scaling, basic process control
- Modbus RTU on RS-485 between two PLCs
Practical Exercises (Labs)
- Lab 4.1: Three-input motor start/stop with seal-in contact
- Lab 4.2: Traffic light controller with cyclic timer sequence
- Lab 4.3: Tank level controller in Structured Text with PID block
- Lab 4.4: 4-20 mA pressure sensor → PLC → HMI scaled display
- Lab 4.5: Two PLCs exchanging data over Modbus RTU
Learning Outcome
By the end of Week 1 you can wire, program and defend a production-grade PLC starter circuit and a tank-level PID loop on a real Delta DVP or Siemens S7-1200.
Industry Application
This is the bedrock skill at Tata Steel’s conveyor lines, ITC’s paper-mill mixers, Jain Irrigation’s pump houses and every CNC retrofit project at MSMEs across Pune, Chennai and Coimbatore.
Week 2 - SCADA, HMI & Industrial Communication (Days 143-149)
Operators don’t look at PLCs - they look at screens. Week 2 trains you to design those screens to the ISA-101 standard, and to wire the data backbone (OPC-UA, Modbus TCP, industrial Ethernet) that feeds them.
Topics Covered
- SCADA architecture: tags, drivers, historians, alarms
- HMI design principles per ISA-101
- OPC-UA information model, sessions and subscriptions
- Modbus TCP deep dive and function codes
- Industrial Ethernet, PROFINET and EtherNet/IP overview
- Alarming, trending and historisation strategies
Practical Exercises (Labs)
- Lab 4.6: Bottling line HMI with start/stop/jog/alarms
- Lab 4.7: Raspberry Pi OPC-UA client → MQTT bridge
- Lab 4.8: ESP32 as Modbus TCP master polling a PLC
- Lab 4.9: SCADA alarms and 30-day historian configuration
Learning Outcome
You can design a working SCADA + HMI for a small bottling or batching line, and you can move PLC data into a cloud-friendly MQTT stream via OPC-UA.
Industry Application
This stack underpins SCADA deployments at FMCG plants, water-treatment facilities and the operator consoles inside India’s expanding fertiliser and chemical clusters.
Week 3 - Edge AI Foundations & TinyML (Days 150-156)
Cloud AI is yesterday’s story for most embedded products. Week 3 trains you to train, quantise and deploy neural networks that run inside a microcontroller for milliwatts of power and microjoules per inference.
Topics Covered
- Edge AI vs Cloud AI tradeoffs and TinyML constraints
- ML refresher: features, training, inference, quantisation
- TensorFlow Lite Micro architecture and tensor arenas
- Edge Impulse Studio end-to-end workflow
- Audio AI: MFCC features and keyword spotting
- Vision AI on MCUs with ESP32-S3 and OV2640
- Model optimisation: quantisation, pruning, EON Compiler
Practical Exercises (Labs)
- Lab 4.10: TFLite Micro sine-wave inference on ESP32-S3
- Lab 4.11: 3-class motion classifier with Edge Impulse
- Lab 4.12: Yes/No keyword spotter on a PDM microphone
- Lab 4.13: ESP32-S3 + OV2640 person-detection demo
Learning Outcome
You can take a real-world classification problem, collect data, train a model in Edge Impulse, quantise it to int8, and ship it to a microcontroller with sub-5 ms inference.
Industry Application
This is the pipeline behind Stellapps’ cattle-collar monitoring, smart-city worker-safety wearables, and the wave of in-cabin AI products emerging from Indian EV startups.
Week 4 - Predictive Maintenance & Sensor Fusion (Days 157-163)
Downtime is the single largest cost in Indian manufacturing. Week 4 trains you to detect failure before it happens using vibration, current, thermal and acoustic signals fused at the edge.
Topics Covered
- Predictive vs preventive vs reactive maintenance
- Vibration sensing, FFT, RMS, kurtosis, crest factor
- Anomaly detection with autoencoders and one-class SVMs
- Current signature analysis and thermal-imaging basics
- Multi-sensor fusion strategies
- Time-series pipelines with InfluxDB and Grafana
- Alerting integration: WhatsApp, Telegram, Email
Practical Exercises (Labs)
- Lab 4.14: Motor vibration FFT analysis on ADXL345 + ESP32
- Lab 4.15: Edge Impulse autoencoder anomaly detection
- Lab 4.16: Multi-sensor predictive-maintenance node
- Lab 4.17: InfluxDB + Grafana PdM dashboard with alerts
Learning Outcome
You can stand up a working predictive-maintenance pipeline for a motor or pump, from sensor to dashboard to mobile alert.
Industry Application
This is the exact pattern deployed at Bajaj Auto Pune, the Indian textile-mill PdM rollouts, and the new wave of industrial-AI startups serving MSMEs across the country.
Week 5 - Digital Twins, Cloud Integration & Industry 4.0 Patterns (Days 164-170)
This is the week where everything you have built becomes queryable, governable and operable from anywhere on the planet.
Topics Covered
- Digital Twin concept, ISO 23247, four twin maturity types
- Azure Digital Twins and AWS IoT TwinMaker
- Bidirectional twin sync - cloud commands back to the field
- MES concepts and OEE (Availability × Performance × Quality)
- OT cybersecurity per IEC 62443 and CERT-In guidelines
- Sustainability and ESG dashboards
- RAMI 4.0 and IIRA reference architectures
Practical Exercises (Labs)
- Lab 4.18: Build a digital twin of a conveyor in Azure Digital Twins
- Lab 4.19: Bidirectional twin command (cloud → PLC)
- Lab 4.20: Three-phase energy meter dashboard with CO₂ footprint
Learning Outcome
You can author a DTDL model, instantiate a twin, ingest live telemetry, query it, and round-trip a command back to the physical asset.
Industry Application
Twins of this shape mirror the architectures at Tata Motors’ weld stations and Reliance Jio’s tower-monitoring stack.
Week 6 - Capstone Build, Demo Day & Career Launch (Days 171-180)
The final ten days are dedicated to building, polishing and presenting the capstone — followed by a focused career-prep sprint.
Daily Plan
- Day 171 - Capstone kick-off, charter, BOM and milestone plan
- Day 172 - System architecture review and risk register sign-off
- Day 173 - Build Day 1: hardware integration of PLC + sensors + edge AI
- Day 174 - Build Day 2: firmware, edge AI, Modbus / OPC-UA wiring
- Day 175 - Build Day 3: cloud, twin and Flutter mobile app
- Day 176 - Build Day 4: end-to-end integration and field testing
- Day 177 - Capstone polish: enclosure, documentation, demo video
- Day 178 - Career Day 1: resume, GitHub, LinkedIn portfolio
- Day 179 - Career Day 2: mock interviews and aptitude practice
- Day 180 - Capstone Demo Day in front of an industry panel
Learning Outcome
You walk out of Day 180 with a panel-evaluated Industry 4.0 system, a ready placement dossier, and a recorded 60-second elevator pitch.
Cluster Map
| Cluster | Days | Theme | Headline Lab |
|---|---|---|---|
| Cluster 4.1 - PLC Foundations | 138-142 | Ladder, ST, FBD, Analog I/O, Modbus RTU | Lab 4.1 - Motor Starter With Seal-In Contact |
| Cluster 4.2 - SCADA / HMI / Comms | 143-149 | SCADA, HMI, OPC-UA, Modbus TCP | Lab 4.7 - OPC-UA to MQTT Bridge |
| Cluster 4.3 - Edge AI / TinyML | 150-156 | TFLite Micro, Edge Impulse, Audio + Vision | Lab 4.11 - IMU Motion Classification |
| Cluster 4.4 - Predictive Maintenance | 157-163 | FFT, Anomaly, Sensor Fusion, InfluxDB | Lab 4.15 - Autoencoder PdM |
| Cluster 4.5 - Digital Twins & I4.0 | 164-170 | DTDL, ADT, OEE, IEC 62443, RAMI 4.0 | Lab 4.18 - Conveyor Twin in Azure |
| Cluster 4.6 - Capstone & Career | 171-180 | Build, polish, demo, career launch | Demo Day |
Module-Wise Document - Deep Dive Into Module 4
Below is the full deep-dive companion to the Module 4 syllabus, broken down at the cluster level.
Flagship Lab Snapshots
Lab 4.1 - Three-Input Motor Starter With Seal-In Contact
Skill focus: IEC 61131-3 Ladder Diagram, input mapping, scan cycle behaviour.
Why it matters: This single rung is the most common opening question in any PLC interview in India. Master it and the rest of factory automation gets dramatically easier.
Lab 4.11 - IMU Motion Classification With Edge Impulse
Skill focus: Data collection, spectral feature extraction, quantisation, TFLite Micro deployment on ESP32-S3.
Why it matters: This pipeline is the foundation of cattle-monitoring collars, elderly fall-detection wearables and construction-worker safety bands deployed across India today.
Lab 4.18 - Conveyor Digital Twin In Azure Digital Twins
Skill focus: DTDL authoring, Azure IoT Hub provisioning, Azure Function bridge, twin query language, command round-trip.
Why it matters: This architecture mirrors what major Indian OEMs deploy at every weld station and what telecom operators run for tower-level monitoring.
Capstone Variants
Agriculture 4.0 - Precision Greenhouse Command Center
PLC-controlled drip-irrigation valves, edge-AI plant-stress classifier on leaf images, OPC-UA to Pi gateway, Azure Digital Twin and a Flutter operator app. Deployable verbatim in Maharashtra and Tamil Nadu polyhouse farms.
Manufacturing 4.0 - Predictive Maintenance For A Conveyor Line
PLC conveyor with sorting actuator, ADXL345 vibration and ACS712 current at the edge, TFLite Micro anomaly model, Modbus TCP to Node-RED, InfluxDB + Grafana, an Azure twin and a Flutter alerts app for maintenance technicians.
Defense 4.0 - Hardened Edge AI Sentry Node
STM32 controller in a ruggedised enclosure, acoustic AI for vehicle / drone / weapon sounds, encrypted LoRa to a command-post Pi gateway, self-hosted air-gapped ThingsBoard twin and a mTLS-protected operator app.
Transport 4.0 - EV Battery Telematics & Driver Behavior
STM32 BMS with CAN-bus cell monitoring, ESP32-S3 driver-behavior classifier, 4G uplink to an Azure twin and a Flutter fleet-manager app showing pack health, predicted range and per-trip driver scores.
Capstone Rubric (200 marks)
| Dimension | Marks |
|---|---|
| System Architecture | 25 |
| Hardware Build | 20 |
| Firmware | 20 |
| Edge AI Component | 20 |
| Cloud / Twin | 20 |
| Mobile / Web App | 15 |
| Security | 15 |
| Documentation | 15 |
| Demo & Communication | 25 |
| Industry Relevance | 15 |
| Innovation / Stretch | 10 |
Curriculum Framework
The framework formalises how learning is structured, sequenced and assessed across Module 4. Every learner moves through identical stages with consistent rubrics, ensuring that a certificate from any cohort means exactly the same thing.
Learning Stages
| Stage | Duration | What Happens |
|---|---|---|
| Concept Briefing | 12-15 min/day | Theory delivered just-in-time with whiteboard sketches and datasheet excerpts |
| Demo & Live Code | 10-12 min/day | Trainer-led live coding or wiring while learners set up benches |
| Hands-On Lab | 45 min/day | Pair work with one driver and one navigator; every lab logged |
| Debug & Discussion | 10-12 min/day | Peer code review and common-error walkthroughs |
| Reflection & Logbook | 5-6 min/day | Photos, BOMs and learnings captured for the placement portfolio |
Assessment Structure
| Component | Weight |
|---|---|
| Daily Lab Logs | 10% |
| Weekly Vivas | 10% |
| Mid-Module Quiz | 10% |
| Mini Projects | 20% |
| Capstone Project | 40% |
| Attendance & Conduct | 10% |
Theory vs Practical Breakdown
- 70% practical (≈ 47 hours) - labs, capstone build, debugging sessions
- 30% theory (≈ 20.5 hours) - Industry 4.0 concepts, standards, datasheets, design decisions
Project-Based Learning Structure
- Every concept is anchored to a deliverable artefact, never just a slide.
- Every lab follows the same 12-section template, from Objective through Industry Use Case.
- Every mini project produces a public GitHub repository with README, schematics and demo video.
- The capstone is a panel-evaluated artefact that becomes the centrepiece of your resume.
Grading Scale
| Grade | Range | Interpretation |
|---|---|---|
| A+ (Distinction) | ≥ 85% | Placement-ready at top-tier employers |
| A (First Class) | 70-84% | Strong industry-ready candidate |
| B (Second Class) | 60-69% | Solid foundation, polish recommended |
| C (Pass) | 50-59% | Eligible for certification, mentorship advised |
| Reattempt | < 50% | Repeat module with mentor support |