{"product_id":"tinyml-hvac-monitor-kit-with-arduino-nano-predict-failures","title":"TinyML HVAC Monitor Kit with Arduino Nano - Predict Failures","description":"\u003ch1\u003eTinyML HVAC Monitor Kit: Predict Failures with Arduino Nano \u0026amp; MPU6050\u003c\/h1\u003e\n\n\u003cp class=\"value-summary\"\u003eEvery part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.\u003c\/p\u003e\n\n\u003cdiv class=\"specs-strip\"\u003e\n  \u003cspan\u003e\u003cstrong\u003eDifficulty:\u003c\/strong\u003e Advanced\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eBuild Time:\u003c\/strong\u003e 6-8 hrs\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eAge:\u003c\/strong\u003e 18-21\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eSkill:\u003c\/strong\u003e TinyML Model Deployment\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eTackle predictive maintenance for HVAC systems by deploying a machine learning model trained on your PC directly to an Arduino Nano. This advanced kit lets you build a compact, battery-powered monitor that classifies vibration and environmental sensor data in real time with 96% accuracy, enabling early detection of compressor or fan imbalances-ideal for industrial IoT capstones and Smart India Hackathon hardware tracks.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou'll assemble a portable device that attaches to an air handling unit or chiller. Using the MPU6050 accelerometer\/gyroscope and DHT22 temperature\/humidity sensor, the Nano captures data, runs a pre-trained TinyML model, and shows the classification result-normal operation, early imbalance, or critical fault-on the OLED display. All enclosed in a rugged ABS box for field testing.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eTraining a TinyML classification model using Edge Impulse or TensorFlow Lite Micro on your PC\u003c\/li\u003e\n  \u003cli\u003eDeploying an optimized model to an Arduino Nano with limited flash and RAM\u003c\/li\u003e\n  \u003cli\u003eInterfacing MPU6050 and DHT22 sensors over I2C for multi-modal data capture\u003c\/li\u003e\n  \u003cli\u003eImplementing real-time inference on an embedded device and visualizing results on an OLED\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003eKit Contents\u003c\/h2\u003e\n\u003ctable\u003e\n  \u003cthead\u003e\u003ctr\u003e\n\u003cth\u003eComponent\u003c\/th\u003e\n\u003cth\u003eQuantity\u003c\/th\u003e\n\u003c\/tr\u003e\u003c\/thead\u003e\n  \u003ctbody\u003e\n    \u003ctr\u003e\n\u003ctd\u003eArduino Nano\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eMPU6050\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eDHT22\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e0.96in OLED\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e3.7V LiPo 500mAh\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eTP4056 Module\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e4.7k? Resistors\u003c\/td\u003e\n\u003ctd\u003e5\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e100nF Capacitors\u003c\/td\u003e\n\u003ctd\u003e5\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003ePCB Prototype Board\u003c\/td\u003e\n\u003ctd\u003e2\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eABS Enclosure Box\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eSoldering Iron\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eSolder Wire\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n  \u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eWhy Buy This Kit Instead of Sourcing Parts Separately\u003c\/h2\u003e\n\u003ctable\u003e\n  \u003cthead\u003e\u003ctr\u003e\n\u003cth\u003eFactor\u003c\/th\u003e\n\u003cth\u003eSourcing Separately\u003c\/th\u003e\n\u003cth\u003eCompoden Kit\u003c\/th\u003e\n\u003c\/tr\u003e\u003c\/thead\u003e\n  \u003ctbody\u003e\n    \u003ctr\u003e\n\u003ctd\u003eCompatibility checks\u003c\/td\u003e\n\u003ctd\u003eYou verify every part\u003c\/td\u003e\n\u003ctd\u003ePre-tested as a system\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eBuild support\u003c\/td\u003e\n\u003ctd\u003eForums and scattered tutorials\u003c\/td\u003e\n\u003ctd\u003eAI companion trained on this exact project\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eTime to first working build\u003c\/td\u003e\n\u003ctd\u003eDays of debugging\u003c\/td\u003e\n\u003ctd\u003eHours, with step-by-step guidance\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eShipping coordination\u003c\/td\u003e\n\u003ctd\u003eMultiple sellers, multiple delays\u003c\/td\u003e\n\u003ctd\u003eOne shipment from Bengaluru in 3-5 days\u003c\/td\u003e\n\u003c\/tr\u003e\n  \u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eWho This Kit Is For\u003c\/h2\u003e\n\u003cp\u003eThis kit is built for final-year B.Tech students of ECE, EEE, or Mechatronics tackling industrial IoT capstone projects, Smart India Hackathon teams aiming for hardware tracks, and young engineers at IIT, NIT, VIT, or BITS Pilani who want hands-on experience deploying TinyML on microcontrollers. If you need a working predictive maintenance demo for your resume or hackathon pitch, this is your project.\u003c\/p\u003e\n\n\u003ch2\u003eBuilt and Backed by Compoden\u003c\/h2\u003e\n\u003cp\u003eEvery Compoden kit ships with an AI build companion trained on this exact project - accessible via a QR code on the box, with WhatsApp and email backup. We've spent 10 years building projects for makers, schools, and institutions across India. If a part fails because of a manufacturing defect, replace it free within 7 days.\u003c\/p\u003e\n\n\u003cdetails\u003e\u003csummary\u003eWhat if I get stuck during the build?\u003c\/summary\u003e\u003cp\u003eOur AI companion, accessed via the QR code, walks you through model training and deployment step-by-step. If needed, you can also reach us on WhatsApp for personal guidance.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDo I need prior machine learning experience?\u003c\/summary\u003e\u003cp\u003eSome familiarity with Python is helpful for training the model on your PC, but the AI companion provides a ready-to-use notebook. The embedded C++ code for the Nano is pre-written and well-commented.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I modify the model for other industrial equipment?\u003c\/summary\u003e\u003cp\u003eAbsolutely. The kit's framework is intentionally generic; by collecting your own data, you can retrain the TinyML model to classify faults in pumps, conveyors, or generators. The AI companion includes tips on data capture.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eHow long does the battery last during continuous monitoring?\u003c\/summary\u003e\u003cp\u003eWith the 500mAh LiPo and optimized sleep intervals, the monitor can run for approximately 8-10 hours of continuous classification, perfect for a single shift of fieldwork or a day-long hackathon demo.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eHVAC - Tiny ML model trained on PC deployed to Nano. Classifies sensor data in real time with 96% accuracy.\u003c\/p\u003e\n  \u003ch4\u003eWhat's in this kit\u003c\/h4\u003e\n  \u003cul\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/nano-r3-ch340-development-board-arduino-compatible-no-cable\"\u003eArduino Nano\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/mpu6050-imu-module-6-axis-gyro-accelerometer-for-arduino\"\u003eMPU6050\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/dht22-temperature-humidity-sensor-module-accurate-readings\"\u003eDHT22\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/096in-oled-display-128x64-i2cspi-for-arduino-raspberry-pi\"\u003e0.96in OLED\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/37v-30c-1000mah-lipo-battery-yy802542-for-drones\"\u003e3.7V LiPo 500mAh\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/tp4056-1a-li-ion-charger-module-with-protection-micro-usb\"\u003eTP4056 Module\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/resistor-variety-pack-100-pcs-10-values-14w-carbon-film\"\u003e4.7k? Resistors\u003c\/a\u003e x5\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/capacitor-variety-pack-6-values-100nf-to-470uf-30-pieces\"\u003e100nF Caps\u003c\/a\u003e x5\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/esp-wroom-32-breakout-board-pcb-55x52mm\"\u003ePCB Prototype Board\u003c\/a\u003e x2\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/official-raspberry-pi-4-abs-case-enclosure-redwhite\"\u003eABS Enclosure Box\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/soldering-kit-25w-with-solder-wire-flux-paste-compoden\"\u003eSoldering Iron\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/soldering-kit-25w-with-solder-wire-flux-paste-compoden\"\u003eSolder Wire\u003c\/a\u003e\u003c\/li\u003e\n  \u003c\/ul\u003e\n\u003c\/div\u003e\n\n\u003cscript type=\"application\/ld+json\"\u003e\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What is included in the HVAC Performance Monitor Kit with Arduino Nano + MPU6050?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The HVAC Performance Monitor Kit with Arduino Nano + MPU6050 includes all components needed: Arduino Nano, MPU6050, DHT22, 0.96in OLED, 3.7V LiPo 500mAh and more. Everything is pre-tested for compatibility and shipped from Bengaluru, India.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What skill level is required for the HVAC Performance Monitor Kit with Arduino Nano + MPU6050?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Advanced level makers, suitable for ages 18-21. HVAC - Tiny ML model trained on PC deployed to Nano. Classifies sensor data in real time with 96% accuracy. Estimated build time is 6-8 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the HVAC Performance Monitor Kit with Arduino Nano + MPU6050 online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the HVAC Performance Monitor Kit with Arduino Nano + MPU6050 is available online at Compoden (compoden.in), India's AI-powered electronics and robotics store. Ships from Bengaluru in 1-5 business days across India.\"\n      }\n    }\n  ]\n}\n\u003c\/script\u003e\n\n\u003cscript type=\"application\/ld+json\"\u003e\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"Product\",\n  \"name\": \"HVAC Performance Monitor Kit with Arduino Nano + MPU6050\",\n  \"description\": \"HVAC - Tiny ML model trained on PC deployed to Nano. Classifies sensor data in real time with 96% accuracy.\",\n  \"sku\": \"CDN-KIT-3974\",\n  \"brand\": {\"@type\": \"Brand\", \"name\": \"Compoden\"},\n  \"offers\": {\n    \"@type\": \"Offer\",\n    \"url\": \"https:\/\/compoden.in\/products\/kit-hvac-performance-monitor-kit-with-arduino-nano-plus-mpu6050\",\n    \"priceCurrency\": \"INR\",\n    \"price\": \"3830\",\n    \"availability\": \"https:\/\/schema.org\/InStock\",\n    \"seller\": {\"@type\": \"Organization\", \"name\": \"Compoden\"}\n  },\n  \"category\": \"Mini \u0026 Nano Form Factor\"\n}\n\u003c\/script\u003e\u003cp\u003e\u003cstrong\u003eChoose your assembly option:\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eSoldering Kit\u003c\/strong\u003e - 25W soldering iron, 60\/40 solder wire, flux, and small perfboard for permanent assembly.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eBreadboard Combo\u003c\/strong\u003e - 800-point full-size breadboard with 65-piece jumper wire pack for solderless prototyping.\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Compoden","offers":[{"title":"Clone \/ Soldering Kit","offer_id":53463936172397,"sku":"CDN-KIT-3974-CL-SLD","price":3140.0,"currency_code":"INR","in_stock":true},{"title":"Clone \/ Breadboard Combo","offer_id":53463936205165,"sku":"CDN-KIT-3974-CL-BB","price":2610.0,"currency_code":"INR","in_stock":true},{"title":"R3 Original \/ Soldering Kit","offer_id":53463936237933,"sku":"CDN-KIT-3974-R3-SLD","price":5580.0,"currency_code":"INR","in_stock":true},{"title":"R3 Original \/ Breadboard Combo","offer_id":53463936270701,"sku":"CDN-KIT-3974-R3-BB","price":5040.0,"currency_code":"INR","in_stock":true},{"title":"R4 WiFi \/ Soldering Kit","offer_id":53463936303469,"sku":"CDN-KIT-3974-R4-SLD","price":4900.0,"currency_code":"INR","in_stock":true},{"title":"R4 WiFi \/ Breadboard Combo","offer_id":53463936336237,"sku":"CDN-KIT-3974-R4-BB","price":4370.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0999\/3997\/5533\/files\/kit-hvac-performance-monitor-kit-with-arduino-nano-plus-mpu6050.png?v=1781949706","url":"https:\/\/compoden.com\/products\/tinyml-hvac-monitor-kit-with-arduino-nano-predict-failures","provider":"Compoden","version":"1.0","type":"link"}