AI RFID Inventory Management System — Full Project Documentation
Below is a complete project structure for an AI-powered RFID inventory system using ESP32 + RFID + n8n + AI Agent + Telegram voice alerts + Google Sheets + ThingSpeak/cloud dashboard.
1. Project Overview
The system automatically identifies inventory using RFID tags, processes the readings through an ESP32, sends data to n8n, stores inventory records in Google Sheets, visualizes sensor/inventory data on ThingSpeak, and uses an AI Agent to analyze events and generate alerts.
Main functions
-
RFID-based item identification
-
Automatic inventory counting
-
ESP32 IoT gateway
-
Wi-Fi/cloud connectivity
-
n8n workflow automation
-
AI-powered inventory analysis
-
Low-stock prediction
-
Missing/unauthorized-item detection
-
Telegram notifications
-
Telegram voice alerts
-
Google Sheets inventory database
-
ThingSpeak dashboard
-
Web-based inventory dashboard
-
Automated reports and summaries
2. Overall Architecture
┌──────────────────────┐
│ RFID TAGS │
│ Item ID / UID Data │
└──────────┬───────────┘
│
▼
┌──────────────────────┐
│ RFID RC522 │
│ RFID Reader │
└──────────┬───────────┘
│ SPI
▼
┌──────────────────────┐
│ ESP32 │
│ RFID + Wi-Fi + IoT │
└──────────┬───────────┘
│ HTTPS / MQTT
▼
┌──────────────────────┐
│ n8n │
│ Automation Workflow │
└──────────┬───────────┘
│
┌─────────────────┼─────────────────┐
▼ ▼ ▼
┌────────────────┐ ┌────────────────┐ ┌────────────────┐
│ Google Sheets │ │ AI Agent │ │ ThingSpeak │
│ Inventory DB │ │ Analysis/Logic │ │ Cloud Dashboard│
└────────────────┘ └───────┬────────┘ └────────────────┘
│
▼
┌─────────────────┐
│ Telegram │
│ Text + Voice │
│ Alerts │
└─────────────────┘
3. Hardware Required
| Component | Purpose |
|---|---|
| ESP32 DevKit | Main IoT controller |
| RC522 RFID reader | Reads RFID tags |
| RFID cards/tags | Inventory identification |
| OLED/LCD | Local status display |
| Buzzer | Local alarm |
| LEDs | Status indication |
| Push button | Manual inventory operation |
| Wi-Fi | Internet connection |
| 5V power supply | ESP32 power |
| Jumper wires | Connections |
| Breadboard/PCB | Prototype |
Optional:
-
ESP32-S3
-
Multiple RFID readers
-
Load cell + HX711
-
DHT22
-
IR sensor
-
GPS
-
Barcode scanner
-
Relay
-
Servo
-
Camera
4. RFID Inventory Concept
Every inventory item receives an RFID tag.
Example:
RFID UID: A3 7B 91 2C
↓
Item ID: ITEM-001
↓
Product: Arduino ESP32
↓
Category: Electronics
↓
Quantity: 25
↓
Minimum Stock: 5
When the tag is detected, ESP32 sends:
{
"device_id": "ESP32-001",
"rfid_uid": "A37B912C",
"timestamp": "2026-09-28T20:30:00",
"event": "RFID_DETECTED"
}
5. RC522–ESP32 Wiring
Use the ESP32's VSPI pins.
| RC522 | ESP32 |
|---|---|
| SDA/SS | GPIO 5 |
| SCK | GPIO 18 |
| MOSI | GPIO 23 |
| MISO | GPIO 19 |
| IRQ | Not connected |
| GND | GND |
| RST | GPIO 22 |
| 3.3V | 3.3V |
Important: RC522 is a 3.3 V device. Do not power the RC522 from 5 V.
6. Basic Circuit Diagram
ESP32
┌──────────────────┐
│ │
GPIO 5 ──┤ SS │
GPIO 18 ──┤ SCK │
GPIO 23 ──┤ MOSI │
GPIO 19 ──┤ MISO │
GPIO 22 ──┤ RST │
GND ─┤ GND │
3.3V ─┤ 3V3 │
│ │
└──────────────────┘
│ │ │ │ │
│ │ │ │ │
▼ ▼ ▼ ▼ ▼
┌─────────────┐
│ RC522 │
│ │
│ SDA │
│ SCK │
│ MOSI │
│ MISO │
│ RST │
│ GND │
│ 3.3V │
└─────────────┘
Optional indicators:
ESP32 GPIO 2 ───► GREEN LED ───► GND
ESP32 GPIO 4 ───► RED LED ─────► GND
ESP32 GPIO 15 ───► Buzzer ─────► GND
Use appropriate current-limiting resistors for LEDs.
7. Software Architecture
ESP32 Firmware
│
├── RFID Driver
├── Wi-Fi Manager
├── JSON Generator
├── HTTP Client
└── Local Alert
│
▼
n8n Webhook
│
▼
Data Validation
│
▼
Inventory Lookup
│
┌──────┴──────┐
▼ ▼
Known Item Unknown RFID
│ │
▼ ▼
Update Stock Security Alert
│ │
└──────┬──────┘
▼
AI Agent
│
┌──────┼────────┐
▼ ▼ ▼
Predict Analyze Recommend
│ │ │
└──────┼────────┘
▼
Google Sheets
│
┌──────┴───────┐
▼ ▼
ThingSpeak Telegram
Dashboard Notification
│
▼
Voice Alert
8. ESP32 Arduino Code
Install:
-
ESP32 board package
-
MFRC522 library
-
WiFi library
-
HTTPClient library
-
ArduinoJson library
Example firmware:
#include <WiFi.h>
#include <HTTPClient.h>
#include <SPI.h>
#include <MFRC522.h>
#include <ArduinoJson.h>
#define SS_PIN 5
#define RST_PIN 22
MFRC522 rfid(SS_PIN, RST_PIN);
const char* WIFI_SSID = "YOUR_WIFI";
const char* WIFI_PASSWORD = "YOUR_PASSWORD";
const char* WEBHOOK_URL =
"https://YOUR_N8N_SERVER/webhook/rfid-inventory";
#define GREEN_LED 2
#define RED_LED 4
#define BUZZER 15
void setup() {
Serial.begin(115200);
pinMode(GREEN_LED, OUTPUT);
pinMode(RED_LED, OUTPUT);
pinMode(BUZZER, OUTPUT);
SPI.begin();
rfid.PCD_Init();
WiFi.begin(WIFI_SSID, WIFI_PASSWORD);
Serial.print("Connecting");
while (WiFi.status() != WL_CONNECTED) {
delay(500);
Serial.print(".");
}
Serial.println();
Serial.println("WiFi connected");
Serial.println(WiFi.localIP());
}
String getUID() {
String uid = "";
for (byte i = 0; i < rfid.uid.size; i++) {
if (rfid.uid.uidByte[i] < 0x10)
uid += "0";
uid += String(
rfid.uid.uidByte[i],
HEX
);
}
uid.toUpperCase();
return uid;
}
void sendRFID(String uid) {
if (WiFi.status() != WL_CONNECTED) {
return;
}
HTTPClient http;
http.begin(WEBHOOK_URL);
http.addHeader(
"Content-Type",
"application/json"
);
StaticJsonDocument<512> doc;
doc["device_id"] = "ESP32-001";
doc["rfid_uid"] = uid;
doc["event"] = "RFID_DETECTED";
doc["device_ip"] = WiFi.localIP().toString();
String payload;
serializeJson(doc, payload);
int response =
http.POST(payload);
Serial.print("HTTP Response: ");
Serial.println(response);
if (response >= 200 && response < 300) {
digitalWrite(GREEN_LED, HIGH);
tone(BUZZER, 2000, 100);
delay(200);
digitalWrite(GREEN_LED, LOW);
} else {
digitalWrite(RED_LED, HIGH);
tone(BUZZER, 500, 500);
delay(500);
digitalWrite(RED_LED, LOW);
}
http.end();
}
void loop() {
if (!rfid.PICC_IsNewCardPresent())
return;
if (!rfid.PICC_ReadCardSerial())
return;
String uid = getUID();
Serial.print("RFID: ");
Serial.println(uid);
sendRFID(uid);
rfid.PICC_HaltA();
delay(1500);
}
9. n8n Automation Workflow
The central automation can be:
Webhook
│
▼
Validate JSON
│
▼
Extract RFID UID
│
▼
Google Sheets Lookup
│
▼
IF Item Exists?
/ \
YES NO
│ │
▼ ▼
Update Security
Stock Alert
│ │
▼ ▼
AI Agent Telegram
│
▼
Inventory Analysis
│
├── Low stock?
├── Abnormal usage?
├── Missing item?
├── Reorder required?
└── Daily summary?
│
▼
Google Sheets
│
▼
ThingSpeak
│
▼
Telegram
10. n8n Nodes
Recommended nodes:
-
Webhook
-
Set
-
Code
-
Google Sheets
-
IF
-
AI Agent
-
HTTP Request
-
Telegram
-
Google Sheets Update
-
Schedule Trigger
Example:
[Webhook]
↓
[Validate RFID]
↓
[Google Sheets Lookup]
↓
[IF Item Exists]
↙ ↘
YES NO
↓ ↓
[Update] [Telegram]
↓
[AI Agent]
↓
[Inventory Decision]
↓
[Google Sheets]
↓
[ThingSpeak]
↓
[Telegram]
11. Google Sheets Database
Create a spreadsheet named:
AI_RFID_INVENTORY
Sheet: Inventory
| RFID_UID | Item_ID | Product | Category | Quantity | Min_Stock | Location | Status |
|---|---|---|---|---|---|---|---|
| A37B912C | ITEM001 | ESP32 | Electronics | 25 | 5 | Rack-A1 | OK |
| B52190AA | ITEM002 | RFID Card | Electronics | 100 | 20 | Rack-A2 | OK |
Sheet: Transactions
| Timestamp | RFID | Item | Event | Quantity | Device |
|---|---|---|---|---|---|
| 2026-09-28 20:00 | A37B912C | ESP32 | IN | 1 | ESP32-001 |
Sheet: Alerts
| Time | Type | RFID | Message | Severity |
|---|---|---|---|---|
| 20:05 | LOW_STOCK | A37B912C | ESP32 stock low | HIGH |
12 . AI Agent
The AI Agent should not directly control physical hardware without validation. Instead, it analyzes structured inventory data and returns a controlled decision .
Example AI input:
{
"item": "ESP32",
"quantity": 4,
"minimum_stock": 5,
"daily_usage": 2,
"last_7_days_usage": 14
}
AI output:
{
"status": "LOW_STOCK",
"risk": "HIGH",
"estimated_days_remaining": 2,
"recommendation": "Create replenishment request"
}
13 . AI Agent Prompt
You are an Inventory Management AI Agent.
Your task is to analyze RFID inventory events.
Available information:
- RFID UID
- Item ID
- Product name
- Current quantity
- Minimum stock
- Historical usage
- Recent transactions
- Location
Rules:
1. Identify low-stock conditions.
2. Identify unusual inventory activity.
3. Calculate approximate inventory consumption.
4. Estimate remaining inventory duration when enough data exists.
5. Identify unknown RFID tags.
6. Recommend replenishment when appropriate.
7. Never invent missing inventory information.
8. Return structured JSON.
9. Do not directly execute dangerous physical actions.
Return:
{
"status": "",
"risk": "",
"analysis": "",
"recommended_action": "",
"alert_required": true/false
}
14. Predictive Analytics
The system becomes more useful when historical RFID transactions are analyzed.
For example:
Monday 10 units
Tuesday 8 units
Wednesday 12 units
Thursday 11 units
Friday 15 units
Average consumption:
Average =
(10 + 8 + 12 + 11 + 15) / 5
= 11.2 units/day
If stock is 45:
Estimated stock life =
45 / 11.2
≈ 4 days
The system can therefore generate:
⚠ INVENTORY FORECAST
Product: ESP32
Current stock: 45
Average daily usage: 11.2
Estimated remaining days: 4
Minimum stock: 20
Recommendation:
Prepare replenishment.
15. Telegram Alerts
n8n can send a Telegram message such as:
🚨 INVENTORY ALERT
Product: ESP32 DevKit
RFID: A37B912C
Current Stock: 4
Minimum Stock: 5
Average Usage: 2/day
Estimated Remaining: 2 days
Risk: HIGH
Recommended Action:
Replenishment required.
16. Telegram Voice Alert
The workflow can be:
Inventory Event
↓
AI Agent
↓
Alert Required?
↓
Generate Message
↓
Text-to-Speech
↓
Audio File
↓
Telegram Send Audio
Example spoken notification:
“Inventory alert. ESP32 stock has fallen below the minimum level. Current stock is four units. Replenishment is recommended.”
17. Unknown RFID Detection
This is an important security feature.
RFID detected
↓
Google Sheets lookup
↓
Is UID registered?
/ \
YES NO
│ │
▼ ▼
Normal Security
operation alert
│
▼
Telegram
Example:
🚨 UNKNOWN RFID
UID: 93A1F27B
Device: ESP32-001
Time: 20:15:31
Location: Warehouse A
Action:
Verify inventory item.
18. ThingSpeak Integration
ThingSpeak can provide IoT visualization.
Possible fields:
Field 1 = Total Inventory
Field 2 = RFID Events
Field 3 = Low Stock Items
Field 4 = Unknown Tags
Field 5 = Daily Consumption
Field 6 = Inventory Risk
Example:
THINGSPEAK
┌─────────────────────┐
│ Total Items: 1,245 │
│ RFID Events: 328 │
│ Low Stock: 7 │
│ Unknown: 2 │
└─────────────────────┘
19. Web Dashboard
A simple webpage can communicate with the backend:
┌──────────────────────────────────────────────┐
│ AI RFID INVENTORY DASHBOARD │
├──────────────────────────────────────────────┤
│ │
│ Total Items RFID Events Low Stock │
│ 1,245 328 7 │
│ │
├──────────────────────────────────────────────┤
│ Inventory Status │
│ │
│ ESP32 ████████████████ 45 │
│ RFID Cards ██████████████████ 100 │
│ Sensors ████████ 18 │
│ │
├──────────────────────────────────────────────┤
│ AI FORECAST │
│ │
│ ESP32: 4 days remaining │
│ Sensors: 8 days remaining │
│ │
├──────────────────────────────────────────────┤
│ Recent Alerts │
│ │
│ 🔴 ESP32 low stock │
│ 🟡 Unknown RFID detected │
│ 🟢 Inventory updated │
└──────────────────────────────────────────────┘
20. Example HTML Dashboard
<!DOCTYPE html>
<html>
<head>
<title>AI RFID Inventory</title>
<style>
body {
font-family: Arial;
background: #101820;
color: white;
margin: 30px;
}
.dashboard {
display: grid;
grid-template-columns:
repeat(3, 1fr);
gap: 20px;
}
.card {
background: #1d2a35;
padding: 25px;
border-radius: 15px;
}
.number {
font-size: 35px;
color: #00e5ff;
}
.alert {
color: #ff5252;
}
</style>
</head>
<body>
<h1>AI RFID Inventory Dashboard</h1>
<div class="dashboard">
<div class="card">
<h3>Total Inventory</h3>
<div class="number" id="inventory">
0
</div>
</div>
<div class="card">
<h3>RFID Events</h3>
<div class="number" id="events">
0
</div>
</div>
<div class="card">
<h3>Low Stock</h3>
<div class="number alert" id="lowstock">
0
</div>
</div>
</div>
<script>
async function loadDashboard() {
const response =
await fetch(
"https://YOUR-N8N-SERVER/webhook/dashboard"
);
const data =
await response.json();
document.getElementById(
"inventory"
).innerText = data.inventory;
document.getElementById(
"events"
).innerText = data.events;
document.getElementById(
"lowstock"
).innerText = data.low_stock;
}
loadDashboard();
setInterval(
loadDashboard,
30000
);
</script>
</body>
</html>
21. Complete Data Flow
RFID TAG
│
▼
┌───────────┐
│ RC522 │
└─────┬─────┘
│
▼
┌───────────┐
│ ESP32 │
└─────┬─────┘
│
Wi-Fi / HTTPS
│
▼
┌───────────┐
│ n8n │
└─────┬─────┘
│
Validate Event
│
▼
Google Sheets
│
▼
Inventory
Lookup
│
┌────────┴────────┐
│ │
Known Unknown
│ │
▼ ▼
Update Record Security Alert
│
▼
AI Agent
│
┌──────┼───────┐
│ │ │
▼ ▼ ▼
Forecast Risk Recommendation
│ │ │
└──────┼───────┘
▼
Alert Decision
│
┌─────┴─────┐
▼ ▼
Dashboard Telegram
│
┌──────┴──────┐
▼ ▼
Text Voice
Alert Alert
22. n8n Workflow for Low Stock
RFID Webhook
│
▼
Read Inventory
│
▼
Calculate Stock
│
▼
Quantity < Minimum?
/ \
YES NO
│ │
▼ ▼
Generate AI Continue
Analysis
│
▼
Generate Alert
│
├──────────────► Google Sheets
│
├──────────────► ThingSpeak
│
└──────────────► Telegram
│
▼
Voice Alert
23. Daily AI Report
Use an n8n Schedule Trigger:
Every day at 8:00 PM
↓
Retrieve today's transactions
↓
Calculate:
- Items consumed
- Items added
- Low-stock products
- Unknown RFID events
- Average consumption
↓
AI Agent
↓
Generate summary
↓
Telegram
Example:
📊 DAILY INVENTORY REPORT
Total RFID Transactions: 328
Items Added: 85
Items Removed: 71
Low Stock:
• ESP32 – 4 units
• RFID Cards – 12 units
Unknown RFID Events:
2
Highest Consumption:
ESP32
AI Forecast:
ESP32 inventory may reach minimum
stock level within approximately 2 days.
System Status:
Operational
24. Agentic IoT Architecture
The project can be described as Agentic IoT because the AI layer does more than simply display sensor readings.
SENSE
↓
RFID + ESP32
↓
UNDERSTAND
↓
n8n + AI Agent
↓
REASON
↓
Predict inventory condition
↓
DECIDE
↓
Generate recommended action
↓
ACT
↓
Telegram / Dashboard / Database
↓
LEARN
↓
Historical inventory data
The important distinction is that the AI agent should operate within defined permissions and validation rules rather than being given unrestricted control over the physical system.
25. Recommended Project Folder
AI-RFID-INVENTORY/
│
├── ESP32/
│ ├── rfid_inventory.ino
│ ├── config.h
│ └── README.md
│
├── n8n/
│ ├── rfid_workflow.json
│ ├── alert_workflow.json
│ └── daily_report.json
│
├── dashboard/
│ ├── index.html
│ ├── style.css
│ └── app.js
│
├── database/
│ ├── inventory.csv
│ └── transactions.csv
│
├── documentation/
│ ├── architecture.md
│ ├── wiring.md
│ └── API.md
│
└── README.md
26. Project Operation — Step by Step
Step 1 — Build hardware
Connect:
ESP32 ↔ RC522
ESP32 ↔ LED
ESP32 ↔ Buzzer
Step 2 — Program ESP32
Install libraries and upload the RFID firmware.
Step 3 — Test RFID
Open Serial Monitor:
RFID Inventory System
WiFi connected
IP: 192.168.1.20
RFID detected:
A37B912C
Step 4 — Create n8n webhook
Example endpoint:
POST /webhook/rfid-inventory
Step 5 — Test webhook
Send:
{
"device_id": "ESP32-001",
"rfid_uid": "A37B912C",
"event": "RFID_DETECTED"
}
Step 6 — Create Google Sheet
Add inventory and transaction tables.
Step 7 — Connect n8n to Google Sheets
Search the RFID UID.
Step 8 — Add AI Agent
Provide historical inventory information to the AI.
Step 9 — Add predictive analysis
Calculate:
Average Daily Consumption
Inventory Remaining
Estimated Days Remaining
Reorder Threshold
Step 10 — Add Telegram
Send text alerts.
Step 11 — Add voice
Convert alert text to speech and send the resulting audio through Telegram.
Step 12 — Add ThingSpeak
Publish inventory statistics.
Step 13 — Create dashboard
Display:
-
Inventory
-
RFID events
-
Low-stock products
-
Unknown RFID tags
-
AI forecast
-
Alerts
Step 14 — Test complete system
RFID
↓
ESP32
↓
n8n
↓
Google Sheets
↓
AI
↓
Prediction
↓
ThingSpeak
↓
Telegram
↓
Voice Alert
27. Example Final Demonstration
Place an RFID-tag ged ESP32 box near the RC522.
The reader detects:
A37B912C
ESP32 sends the event to n8n.
n8n finds:
Product: ESP32
Current quantity: 5
Minimum quantity: 5
Daily consumption: 2
AI determines that inventory is approaching its configured threshold.
The system updates:
Google Sheets
+
ThingSpeak
+
Dashboard
Telegram receives:
⚠️ INVENTORY WARNING
ESP32 stock: 5
Minimum: 5
Usage: 2/day
Inventory has reached
the configured minimum level.
Then the voice notification can say:
“Inventory warning. ESP32 stock has reached
the configured minimum level. Replenishment
should be reviewed.”
This gives you a complete RFID → ESP32 → n8n → AI → predictive analytics → Google Sheets → ThingSpeak → Telegram text/voice alert → web dashboard architecture suitable for a final-year project, IoT demonstration, or prototype deployment.
AI RFID Inventory Management — Mind Map
┌──────────────────────────────┐
│ AI RFID INVENTORY SYSTEM │
└──────────────┬───────────────┘
│
┌─────────────────────────────┼─────────────────────────────┐
│ │ │
▼ ▼ ▼
┌─────────────┐ ┌──────────────┐ ┌──────────────┐
│ HARDWARE │ │ SOFTWARE │ │ AI LAYER │
└──────┬──────┘ └──────┬───────┘ └──────┬───────┘
│ │ │
┌────┼─────┐ ┌─────┼──────┐ ┌─────┼──────┐
│ │ │ │ │ │ │ │ │
▼ ▼ ▼ ▼ ▼ ▼ ▼ ▼ ▼
ESP32 RC522 RFID n8n Google ThingSpeak AI Forecast Analysis
Tags Sheets
│
├── Wi-Fi
├── LED
├── Buzzer
└── OLED/LCD
┌────────────────────────────────┐
│ RFID DATA FLOW │
└───────────────┬────────────────┘
│
▼
RFID Tag Read
│
▼
RC522 Reader
│
▼
ESP32
│
▼
JSON / HTTPS
│
▼
n8n
│
┌───────────┴───────────┐
│ │
▼ ▼
Known RFID Unknown RFID
│ │
▼ ▼
Update Inventory Security Alert
│
▼
AI Agent
│
┌─────────┼─────────┐
│ │ │
▼ ▼ ▼
Stock Usage Risk
Analysis Analysis Analysis
│ │ │
└─────────┼─────────┘
│
▼
Predictive Analytics
│
┌─────────┼──────────┐
│ │ │
▼ ▼ ▼
Low Stock Forecast Reorder
│
▼
Alert System
│
┌────────────────┼────────────────┐
│ │ │
▼ ▼ ▼
Telegram Voice Alert Dashboard
│
▼
Human Decision
┌───────────────────────────────────────────────┐
│ CLOUD LAYER │
└──────────────────────┬────────────────────────┘
│
┌─────────────────┼─────────────────┐
│ │ │
▼ ▼ ▼
Google Sheets ThingSpeak n8n
│ │ │
▼ ▼ ▼
Inventory DB IoT Charts Automation
Transactions Statistics Workflows
Alert History Trends AI Agent
┌───────────────────────────────────────────────┐
│ USER LAYER │
└──────────────────────┬────────────────────────┘
│
┌─────────────────┼─────────────────┐
│ │ │
▼ ▼ ▼
Web Dashboard Telegram Reports
│ │ │
▼ ▼ ▼
Live Inventory Text Alert Daily Report
AI Forecast Voice Alert AI Summary
Stock Status Security Alert Analytics
Simplified project hierarchy
AI RFID INVENTORY
│
├── 1. Hardware
│ ├── ESP32
│ ├── RC522
│ ├── RFID Tags
│ ├── LED
│ ├── Buzzer
│ └── Display
│
├── 2. IoT Communication
│ ├── Wi-Fi
│ ├── HTTP/HTTPS
│ ├── JSON
│ └── n8n Webhook
│
├── 3. Automation
│ ├── n8n
│ ├── Webhook
│ ├── Conditions
│ ├── Google Sheets
│ └── Telegram
│
├── 4. AI
│ ├── AI Agent
│ ├── Stock Analysis
│ ├── Consumption Analysis
│ ├── Forecasting
│ ├── Risk Detection
│ └── Recommendations
│
├── 5. Cloud
│ ├── Google Sheets
│ ├── ThingSpeak
│ └── n8n
│
├── 6. Notifications
│ ├── Telegram Text
│ ├── Telegram Voice
│ ├── Low Stock
│ └── Unknown RFID
│
└── 7. User Interface
├── Web Dashboard
├── Inventory Status
├── AI Forecast
├── Alerts
└── Reports
Project Summary
The proposed project is an AI-powered RFID Inventory Management System combining ESP32, RFID, n8n automation, AI Agent, Google Sheets, ThingSpeak, Telegram, and a web dashboard.
Core workflow
RFID Tag
↓
RC522 RFID Reader
↓
ESP32
↓ Wi-Fi / HTTPS
n8n Automation
↓
Inventory Database
↓
AI Agent
↓
Predictive Analytics
├── Low-stock detection
├── Consumption analysis
├── Inventory forecasting
├── Unknown RFID detection
└── Replenishment recommendation
↓
┌──────────────┬──────────────┬──────────────┐
Google Sheets ThingSpeak Telegram
Database Dashboard Text/Voice
↓
Web Dashboard
Main components
-
ESP32 — reads RFID tags and sends inventory events over Wi-Fi.
-
RC522 — identifies individual inventory items using RFID.
-
n8n — central automation/orchestration layer.
-
AI Agent — analyzes inventory history and generates forecasts/recommendations.
-
Google Sheets — stores inventory, transactions, and alerts.
-
ThingSpeak — provides IoT/cloud visualization.
-
Telegram — delivers real-time text and voice alerts.
-
Web dashboard — displays inventory status, alerts, and AI predictions.
Key features
-
Automatic RFID-based inventory identification.
-
Real-time inventory updates.
-
Low-stock alerts.
-
Unknown/unauthorized RFID detection.
-
Historical consumption tracking.
-
Predictive inventory forecasting.
-
AI-generated recommendations.
-
Telegram text notifications.
-
Telegram voice notifications.
-
Cloud dashboard and web interface.
-
Daily AI-generated inventory reports.
-
Centralized n8n automation.
Hardware
ESP32
RC522 RFID Reader
RFID Tags/Cards
LEDs
Buzzer
OLED/LCD (optional)
Wi-Fi
Power Supply
Software
Arduino IDE
ESP32 Firmware
n8n
Google Sheets
ThingSpeak
Telegram Bot
AI/LLM
HTML/CSS/JavaScript Dashboard
Project outcome
The final system transforms a conventional RFID reader into an agentic IoT inventory platform that can sense inventory, process events, analyze historical data, predict stock conditions, update cloud records, and automatically notify users.
No comments:
Post a Comment