IoT & Embedded projects
ESP32, Arduino and connected devices.
IoT Smart Manhole Cover Monitor with Displacement and Gas Alerts
This project builds an IoT monitor mounted on a manhole cover that watches two hazards: cover displacement or opening (theft,...
IoT Smart Pill Dispenser with Reminders
Smart pill dispenser on ESP32 with an 8-compartment rotating carousel, buzzer reminders and missed-dose alerts to caregivers.
IoT Smart Street Light with Auto Intensity Control
An energy-saving street-light controller that switches lamps on at dusk using an LDR and dims them to about 30% via PWM when...
IoT Smart Switchboard with Energy and Safety Dashboard
This project builds an IoT smart switchboard that replaces a conventional switchboard with relay-controlled sockets, per-sock...
IoT Soil NPK Nutrient Monitor with Fertilizer Advisory Dashboard
This project builds an IoT soil nutrient monitor: a 7-in-1 soil probe measuring nitrogen, phosphorus, potassium, moisture and...
IoT Soil Nutrient Monitor with NPK and pH Sensing
This project builds an IoT soil nutrient monitor that measures nitrogen, phosphorus and potassium with an NPK sensor probe, s...
IoT Soil pH Monitor for Precision Agriculture
Soil pH decides whether fertilizer actually reaches the plant: most crops absorb nutrients best between pH 6.0 and 7.5, yet f...
IoT Solar Panel Soiling Monitor with Cleaning Alert
Dust quietly steals solar output: in dusty regions soiling losses of 5–20% are common, yet rooftop owners clean on a fixed ca...
IoT Structural Health Monitoring System
An IoT structural-health monitoring node that mounts on beams/bridges/buildings, measures vibration (MPU6050) and tilt, strea...
IoT & Embedded guides
All guidesAI Agents on ESP32: Agentic IoT Final-Year Projects
An agentic IoT system observes, reasons, acts, remembers and explains. On ESP32 that means a split architecture: the chip senses and acts while a small local model (Ollama on your laptop) reasons over MQTT — a full LLM needs gigabytes of RAM the chip doesn't have. This guide covers three working patterns (host-reasoned agent, on-device tinyML on ESP32-S3, and a hybrid of both), plus Wi-Fi CSI presence sensing, parts and budget for India, code shapes, and honest limits to state in your report.
Read guideCAN Bus Basics for Students: How ECUs Communicate
CAN bus is the shared network that lets dozens of controllers in a car, EV or robot communicate over two wires. This guide explains message IDs, arbitration, the physical layer, frame structure, error handling and CAN FD, then walks through building a working two-node bench network with an ESP32 and a transceiver.
Read guideDrone Build: Parts Selection Guide
Picking drone parts that actually work together is a sizing problem, not a shopping problem. This guide walks the compatibility chain — frame to props to motors to ESCs to battery — with the thrust math, firmware choices, LiPo safety, and the bench-test order that prevents disasters.
Read guideZigbee vs Thread vs Matter Explained
Zigbee, Thread and Matter are not interchangeable. Learn what each one is (mesh standard vs IP networking layer vs interop application layer), how they stack together, which ESP32 variants support 802.15.4, and how to choose the right one for your smart-home project.
Read guideWatchdog Timers Explained for Embedded Projects
Make deployed devices recover from hangs on their own: how watchdog timers work, the ESP32's task/interrupt/RTC watchdogs, feeding strategies that prove real progress, interaction with deep sleep, reset-cause logging, graceful degradation, and the mistakes behind mysterious resets.
Read guideThingsBoard Dashboard Setup Guide
Build a professional multi-device IoT system with ThingsBoard: device onboarding over MQTT, dashboards with charts and maps, rule chains for alarms and validation, deployment options, and an honest comparison with Node-RED and custom web apps.
Read guideFrequently Asked Questions
Do I get the actual hardware or just the design?
You get everything needed to build it: firmware, wiring diagrams, component list with part numbers, and assembly guidance. Hardware can be procured through us or sourced locally.
Which microcontrollers do you work with?
ESP32, ESP8266, Arduino (Uno, Nano, Mega), Raspberry Pi and STM32, plus common sensors — DHT22, ultrasonic, PIR, soil moisture, current sensors and more.
Can the project connect to a mobile app or cloud dashboard?
Yes — many listings include Blynk, Firebase or MQTT dashboard integration. Custom app requirements can be quoted.
How long does a built-to-order IoT project take?
Typical delivery is 2–4 weeks depending on component availability and complexity. The exact timeline is confirmed in your quotation.
About IoT & Embedded projects
IoT and embedded projects are the most hands-on option for a final-year build. A typical project connects physical sensors and actuators to a microcontroller, moves the data over Wi-Fi to a cloud service, and shows it on a phone app or web dashboard. You end up learning a little of everything: electronics, firmware programming, networking, and basic backend work. That breadth is exactly why these projects are respected, but it is also why they take longer than they look on paper.
What IoT students usually build
The most common builds fall into a few families. Agriculture projects like IoT Smart Irrigation with Soil Moisture read soil moisture levels and switch a water pump automatically, sometimes with a manual override from the app. Surveillance and robotics builds like the ESP32-CAM Surveillance Robot stream video while moving on a small chassis. Access and automation projects like the RFID Smart Toll Collection System read RFID tags to simulate toll deduction and barrier control. City infrastructure ideas like IoT Smart Street Light with Auto Intensity dim LED street lights based on ambient light and motion, which is a neat demonstration of closed-loop control.
Almost all of these share the same skeleton: a microcontroller reads one or more sensors, decides what to do, drives an actuator like a relay or motor driver, and publishes readings to the cloud. If you understand that loop properly, you can adapt it to dozens of problem statements.
Technologies and tools worth learning
Three boards cover nearly every student project. The ESP32 is the workhorse: built-in Wi-Fi and Bluetooth, plenty of GPIO pins, low cost, and strong documentation. Arduino Uno or Nano is friendlier for beginners and perfectly fine when you do not need wireless connectivity. The Raspberry Pi is a small computer rather than a microcontroller, and it earns its place when you need a camera, image processing, or a local server. Our guide ESP32 vs Arduino vs Raspberry Pi: Which Is Best for Final-Year IoT Projects walks through this choice in detail.
On the sensing side, learn a handful of sensors properly rather than ten superficially: soil moisture, DHT22 for temperature and humidity, PIR for motion, ultrasonic for distance, and an LDR for light. The guide How to Choose the Right Sensor for Your IoT Project covers operating voltage, accuracy limits, and calibration, which are the things that actually cause demo-day failures. For communication, MQTT is the standard lightweight protocol for sensor data, while plain HTTP is fine for occasional updates. Two more guides, MQTT for Final-Year IoT Projects: A Practical Student Guide and How to Connect Your IoT Project to the Cloud (MQTT, HTTP, Firebase, Blynk), take you from a bare board to a working dashboard.
Hardware and software, in what proportion
Expect roughly half your time on hardware and half on software. Hardware means wiring on a breadboard or perfboard, a stable power supply, and a presentable enclosure. Plan the power design early: USB power banks sag under motor loads, and brownouts cause the exact kind of intermittent failure that is hardest to debug the night before a demo. Software means firmware in the Arduino IDE or PlatformIO, plus whatever app or dashboard displays the data.
The classic mistake is adding sensors faster than you can debug them. Get one sensor reading reliably, one actuator responding, and the cloud link stable before you add the second feature. A small working system always scores better than a large half-working one.
Choosing the right scope
Be honest about four things: timeline, budget, team size, and skills. Most teams have three to four months of real working time alongside other subjects. A single-ESP32 project with two or three sensors, a relay, and a Blynk dashboard fits that window comfortably. Adding a Raspberry Pi with camera processing roughly doubles the software work, so only take that on if someone on the team is comfortable with Linux and Python.
Component budgets for these builds are usually modest, but order parts early because shipping delays are the most common reason IoT projects slip. Teams of two to four work well: one person owns hardware and wiring, one owns firmware, one owns the app or dashboard, and everyone shares documentation. If nobody on the team has debugged a circuit before, keep the hardware simple and put the complexity in software, where mistakes are cheaper to fix.
A note on how Projectech works
Projectech builds final-year IoT and embedded projects to order, with the hardware assembled, firmware written, and the cloud dashboard configured for your specific topic. Every build comes with a clear explanation of how it works, so you can answer questions about your own project with confidence, along with report and presentation support for your submission.