13

What is VLAN and VLAN Tag/Untag? Basics for Network Setups

by with No Comment CommTech

Still Confused About VLAN? Let’s Clear It Up

You’ve probably heard the term VLAN tossed around in networking conversations, and it might sound technical—but it’s actually pretty straightforward.

Think of a VLAN (Virtual Local Area Network) as a way to split one physical network switch into separate, isolated groups. Imagine you’ve got an 8-port TP-Link or Netgear switch at home. By default, every device plugged into it can talk to every other device.

Now here’s where VLANs come in: you create virtual “walls” between some of those ports. So maybe ports 1–4 are for your work devices, and ports 5–8 are for your smart home gadgets. Even though they’re on the same switch, they can’t see or interfere with each other unless you allow it.

It’s like having two networks in one box—clean, organized, and much more secure.

A. Quick Real-Life Scenario

Let’s say your setup looks like this:

  • VLAN 10: Tech PC, Work-from-home systems
  • VLAN 20: IoT devices, Smart TV
  • VLAN 30: IP Cameras
  • VLAN 40: Guest Wi-Fi users

Now, you’re wiring this to a managed switch (like TL-SG108E), and here’s how you configure the ports:

PortConnected DeviceVLANType
1TP-Link ER605 Router10,20,30,40Tagged (Trunk)
2Work PC10Untagged
3CCTV Camera 130Untagged
4Smart TV20Untagged
5Deco Mesh Node10,20,40Tagged (Trunk)

Tagged means this port carries multiple VLANs, usually used when connecting to routers or mesh nodes.

Untagged means the device on this port is assigned to a single VLAN, like your TV or IP cam. The device doesn’t need to know VLAN stuff—it just connects and works.

B. Some Ground Rules You Must Know

  • Never mix tagged and untagged on the same VLAN ID—you’ll cause mayhem.
  • Access Points need tagged trunks if you want to push multiple SSIDs (like Guest, Home, IoT).
  • Always assign a dedicated VLAN for CCTV if you want peace of mind (and uninterrupted Netflix).

12

Wi-Fi 7 Router for Home & SMB: What You Really Need to Know in 2025

by with No Comment CommTech

Let’s be honest—most people don’t replace their routers until something breaks. But if you’re running a modern home or a small office in 2025, relying on an outdated Wi-Fi 5 or even Wi-Fi 6 router is like driving a Maruti 800 on an expressway built for electric SUVs.

Wi-Fi 7 isn’t just a speed bump. It’s an entirely different league of wireless connectivity—and it’s arriving at the right time, especially for Indian users juggling IoT, CCTV, work-from-home traffic, and even edge-based AI workloads.

What Exactly Is Wi-Fi 7?

Technically called IEEE 802.11be, Wi-Fi 7 brings together everything we wished Wi-Fi 6E could deliver but didn’t quite hit in real-world Indian environments. Think of speeds up to 46 Gbps, better signal reliability, and something called Multi-Link Operation (MLO), which allows your devices to talk over multiple bands at once (like using two express lanes instead of one).

In plain terms: more speed, less lag, and fewer complaints from every member of the house or team.

A. Why This Matters for Indian Homes & Small Businesses

1. Heavy Streaming, Smart Homes, and Workload Collisions

If your home has a Smart TV, 4 IP cameras, a Pi running Home Assistant, and five people on video calls—you’re not a basic user. You’re running a mini data center. Wi-Fi 7 gives that setup breathing room.

2. Managing Dual ISP and WAN Failover

A lot of Indian homes and small offices now combine fiber with 4G/5G as backup. A Wi-Fi 7 router with multi-WAN support doesn’t just keep you online—it can load balance intelligently. No more toggling JioFi manually when Airtel Fiber acts up.

3. Edge AI, IoT, and Local Automations

Many of us are now deploying on-device AI—whether for CCTV analytics, bandwidth prediction, or just smart lighting triggers. Wi-Fi 7’s low latency and better handling of multiple small packets (common with IoT) make automation snappier and more reliable.

B. What to Look for in a Wi-Fi 7 Router

FeatureWhy You Actually Need It
Multi-Link Operation (MLO)Routes traffic over multiple bands at once—great for crowded homes
320 MHz Channel WidthEssential if you have many high-bandwidth devices
4096-QAM ModulationHigher data rate per signal unit (translation: faster real-world speed)
Low Latency & Jitter ControlCrucial for VoIP, Zoom calls, and real-time automations
Multiple WAN/LAN PortsIf you’re doing dual-ISP or VLAN segregation
Mesh SupportMust-have for 2BHK+ homes or multi-floor offices

Top Wi-Fi 7 Routers for Indian Buyers (2025 Update)

These aren’t fantasy picks from US YouTubers—these are models with India availability, vendor support, and strong compatibility with hybrid home-office setups.

ModelPrice (INR)Best For
TP-Link Archer BE800₹35,000All-round performance for smart homes
Asus RT-BE96U₹42,000Heavy parallel workloads & edge deployments
Netgear Nighthawk RS700₹39,000Households with 15+ connected devices
TP-Link Deco BE85 (2-pack)₹50,000Multi-storey homes, offices, or studios
Ubiquiti UniFi U7-Pro₹34,000Users running VLANs, Omada/Unifi environments

💬 Using a TP-Link Deco X50 or ER605 already? The BE85 nodes slot right in.

Real Use Case from a Typical Indian Tech Home

Here’s a setup:

  • 4x IP cameras (streaming 24/7)
  • Raspberry Pi running Pi-hole and Home Assistant
  • 3 smart plugs and 2 IR blasters
  • 1 tech PC training a lightweight ML model
  • Edge AI script reading Speed test logs every 5 mins

Wi-Fi 6 struggled with this. The cameras froze during large downloads. Pi-hole dropped queries under high load. After switching to Wi-Fi 7 with a proper VLAN setup, latency dropped by 40%, OTA updates were seamless, and automations responded instantly.

Wi-Fi 7 isn’t about flexing gigabit speed in a speed test screenshot. It’s about making your entire network invisible—you don’t notice it, because it just works. If your home or office relies on multiple connected devices, automation tools, or edge-based apps, Wi-Fi 7 isn’t overkill—it’s insurance.

8

How to Set Up a Smart Home Network with Edge AI : Step-by-Step Guide (Part 3)

by with No Comment DIY Desk

Welcome to the final part of our Smart Home DIY series. If you’ve been following along, we’ve already built a solid network foundation using a Raspberry Pi, Pi-hole, and Home Assistant. Now, it’s time to take it to the next level: bringing real AI intelligence to your home network—right at the edge.

Why Edge AI, and Why Now?

In a world where latency and privacy matter more than ever, Edge AI offers a game-changing advantage:

  • It runs locally, not in the cloud.
  • It keeps your data private and decisions faster.
  • And it’s customizable to your own routines and behaviors.

This isn’t just automation—this is prediction, inference, and autonomous action at the device level.

Let’s walk through how to build your own bandwidth-predicting AI, run a local LLM (Large Language Model) using Ollama, and even trigger an alert through ESP32-based devices.

A. Build a Python AI Agent (Bandwidth Predictor)

Let’s say you want to know in advance when your internet slows down—maybe around 5 PM, when everyone jumps online. Here’s how to build an AI that learns your network trends.

Step 1: Use Speedtest Logs

*/30 * * * * speedtest-cli >> /home/pi/speedlog.txt

Start by using logs from your Pi:

Step 2: Create the Python Agent

pythonCopyEditimport pandas as pd
from sklearn.linear_model import LinearRegression

data = pd.read_csv('speedlog.csv')  # Format: Time,Speed
model = LinearRegression().fit(data[['Time']], data['Speed'])

predicted = model.predict([[1700]])  # Predict 5PM performance
if predicted[0] < 20:
    print("Warn user: Speed may drop at 5PM")

This script is basic, but powerful—it lets your network learn from patterns. You can expand it with time series or anomaly detection later.

B. Running a Local LLM with Ollama

Want to run a language model like LLaMA2 or Mistral without sending anything to the cloud? Use Ollama.

Step 1: Install and Run

You can now query the model locally, integrate it into scripts, or connect it with Home Assistant for smart responses or triggers.

ollama run llama2

C. Integrate with Home Assistant

Let’s feed the AI’s prediction into your Home Assistant dashboard.

Step 1: Use command_line Sensor

You’ll now see predicted bandwidth results as a sensor in Home Assistant—ready for further automations.

sensor:
  - platform: command_line
    name: Bandwidth Forecast
    command: "python3 /home/pi/ai_agent.py"
    scan_interval: 3600

D. ESP32: Take Action on AI Alerts

Want a physical alert when the model predicts speed issues?

Use ESP32 (with buzzer or LED) via MQTT or GPIO:

  • Connect LED or buzzer
  • Program ESP32 to listen for messages or state changes
  • Trigger alert when forecast drops below threshold

Example: “If bandwidth forecast < 20 Mbps → Flash red LED”

Recap: Why Edge AI is a Game-Changer

✔️ No cloud latency or privacy risk
✔️ Customize actions per your needs
✔️ Empower your router to be smarter than ever
✔️ DIY-friendly, no expensive equipment needed

7

How to Set Up a Smart Home Network with Edge AI : Step-by-Step Guide (Part 2)

by with No Comment DIY Desk

Introduction

In Part 1, we set up a smart edge-powered monitoring system using Raspberry Pi and Pi-hole. Now, let’s take it a step further—by making your network intelligent and automated. Whether it’s blocking internet during bedtime or reacting to internet slowdowns, automation keeps your digital life efficient.

Tools You’ll Need

ComponentDetails
Raspberry Pi 4/3With Raspberry Pi OS Lite installed
Docker InstalledContainerized environment for Home Assistant
TP-Link Deco RouterWith local IP access
Telegram Bot (optional)For automation alerts
Home AssistantSelf-hosted automation hub

Step 1: Install Home Assistant via Docker

Run the following in your Raspberry Pi terminal:

docker run -d –name homeassistant \
–privileged \
–restart=unless-stopped \
-e TZ=Asia/Kolkata \
-v /home/pi/homeassistant:/config \
-p 8123:8123 \
ghcr.io/home-assistant/home-assistant:stable

This sets up Home Assistant in Docker, with data stored in /home/pi/homeassistant.

🔗 Access it via: http://<raspberry_pi_ip>:8123

Step 2: Add TP-Link Deco Router Integration

Inside Home Assistant:

  • Navigate to Settings → Devices & Services → Integrations
  • Search for TP-Link Kasa Smart
  • Add your router’s IP and credentials

✅ This allows Home Assistant to control your Deco mesh router (device block, restart, etc.).

Step 3: Automation – Block Internet at Night

Here’s how to block internet on a child’s device every night at midnight:

Meera: Block Mobile Internet at Night
trigger:
platform: time
at: “00:00:00”
condition: []
action:
service: tplink.set_device_state
data:
device_id: “”
enabled: false
mode: single

Replace <DEVICE_ID> with the actual device ID shown in the Deco integration.

Step 4: Automation – Speed Drop Alert

Automatically notify you if your download speed drops below 20 Mbps:

Meera: Alert on Speed Drop
trigger:
platform: numeric_state
entity_id: sensor.speedtest_download
below: 20
condition: []
action:
service: notify.telegram
data:
message: “Internet speed dropped below 20 Mbps!”
mode: single

Setup Tip: Use Speedtest CLI + sensor integration from Part 1 to track download speed.

Step 5: Visual Automations with Lovelace

Turn automation toggles into visual buttons:

Steps:

  • Go to Overview → Edit Dashboard
  • Add a new Entities Card
  • Include automation toggles like:
    • automation.block_mobile_internet_at_night
    • automation.alert_on_speed_drop

What’s Next?

Now your network isn’t just monitored—it acts on its own. In Part 3, we’ll explore AI integrations—using lightweight LLMs or TTS models to make your router or Raspberry Pi smarter with voice and intent recognition.

📦 Stay tuned for:

  • Edge LLM on Pi (like Whisper, Whisper.cpp)
  • Use cases like offline voice commands
  • YAML for AI triggers

TechieBano.Com | Smart Gear. Smarter Minds.

5A

How to Set Up a Smart Home Network with Edge AI : Step-by-Step Guide (Part 1)

by with No Comment DIY Desk

Introduction

In today’s data-driven world, a basic router can’t keep up with modern demands. Buffering videos, inconsistent speed, and poor control over devices make traditional networks frustrating. That’s where Edge AI and DIY home networking step in.

In this blog series, we’ll build a smart, self-monitoring telecom setup using:

  • A Raspberry Pi
  • Edge AI tools
  • A TP-Link Smart Router
  • And simple scripting

This is Part 1: we’ll cover the setup and monitoring layer. No coding experience? No problem.

1. Tools You’ll Need

ComponentDescriptionBuy Link
Raspberry Pi 4 (2GB or 4GB)Small Linux computerBuy on Amazon
microSD Card (32GB)For OS & logsBuy on Amazon
TP-Link Deco / Archer RouterSmart Router with appBuy on Amazon
Internet ConnectionBroadband or Fiber—
Laptop/PCFor SSH & configuration—

2.Raspberry Pi Setup

Let’s start with the Pi.

  1. Flash Raspberry Pi OS Lite
  • Download Raspberry Pi Imager
  • Select: Raspberry Pi OS Lite (64-bit)
  • Flash to microSD using a card reader
  1. Enable SSH
  • After flashing, open the boot partition
  • Add a blank file named ssh (no extension)
  1. First Boot + Update

Insert SD card, power up, connect to the network.

Login via terminal or SSH:

ssh pi@<raspberry_pi_ip>

Note: #default password: raspberry

Update your Pi:

sudo apt update && sudo apt upgrade -y

3. Installing Pi-hole

Let’s block ads and monitor DNS traffic locally.

Install Pi-hole

curl -sSL https://install.pi-hole.net | bash

Follow the prompts → Choose your network interface → Set a static IP.

Dashboard Setup

Once installed, access:

4.Speedtest Integration (Optional but Awesome)

Want to log your internet speed automatically?

Install CLI Tool

sudo apt install speedtest-cli

Add Cronjob for Auto Logging

crontab -e

Paste this at the end:

*/30 * * * * speedtest-cli >> /home/pi/speedlog.txt

Note: This logs speed every 30 minutes. Use it later for AI analysis in Part 3.

✅ Wrap-Up

You’ve now:

  • Set up your Raspberry Pi
  • Installed Pi-hole to block ads and monitor DNS traffic
  • Configured automatic internet speed logging

Up Next in Part 2:
We’ll add Home Assistant, automate bandwidth alerts, and create smart rules for your devices.

🛠️ TechieBano.Com | Smart Gear. Smarter Minds.

1

Requirement: Running AI Applications on a Home PC

by with No Comment DIY Desk

Why You Should DIY Local AI at Home

Running AI locally means:

  • Total control over your data and models
  • Offline functionality with no internet reliance
  • Zero cloud fees and complete autonomy
  • Fast, responsive performance for automation and learning

Step 1: Prepare Your AI-Capable Home PC

ComponentSuggested SpecsNotes
CPUIntel i7 / Ryzen 7 (or newer)For multithreaded processing
RAM16 GB minimum, 32 GB preferredRequired for large models
GPUNVIDIA RTX 3060 / 4060+ (with CUDA)Core accelerator for AI workloads
Storage1TB SSD (NVMe)Faster model and data loading
Operating SysUbuntu 22.04 LTS / Windows 11 ProLinux recommended for AI dev
CoolingDual-fan or liquid coolingPrevents throttling during long runs

Step 2: Install Key AI Tools

✅ For Development & Automation

  • Python + Anaconda or venv
  • PyTorch / TensorFlow (GPU enabled)
  • CUDA Toolkit + cuDNN
  • JupyterLab or VS Code
  • Docker + Git (version control)

✅ For On-Device LLMs

  • Ollama (CLI)
  • LM Studio (GUI)
  • Text Generation WebUI
  • LangChain / Haystack (for pipelines)

✅ For Smart Home Projects

  • Home Assistant (with Docker)
  • Node-RED (logic builder)
  • Mosquitto MQTT (for IoT control)
  • YOLOv8 + OpenCV (for vision-based automation)

Step 3: AI Projects You Can DIY

Use CaseTools Required
Offline ChatbotPhi-2, Ollama, LM Studio
Voice AssistantWhisper.cpp + Node-RED
CCTV SurveillanceYOLOv8 + OpenCV + MQTT
Smart Light/FanHome Assistant + Node-RED
PDF Q&A SystemLangChain + Text Embedding + Vector Store
Writing AssistantText Generation WebUI

Step 4: Get Your Models from Trusted Sources

Model TypeSource
LLMsHugging Face, LM Studio, Ollama
Audio/STTWhisper.cpp
Vision/YOLOUltralytics, OpenCV
Diffusion/ImageAUTOMATIC1111, Diffusers
Agent FrameworkCrewAI, AutoGPT, LangChain

Step 5: Tips for Privacy & Optimization

Privacy Practices

  • Use offline-only software
  • Block outbound traffic via your firewall
  • Run Docker containers to isolate AI environments

Performance Tweaks

  • Use quantized models (.int4, .gguf)
  • Load frequently used models into RAMdisk
  • Use nvidia-smi to monitor GPU temperature & memory
  • Set up power-saving automations when idle

Step 6: Community Resources & Learning

  • r/LocalLLaMA (Reddit community)
  • Discord: Ollama, LM Studio, Home Assistant forums
  • GitHub: Search “local-llm”, “smart-home-automation”
  • Indian Telegram/WhatsApp AI user groups

Build, Tinker, Share

It’s a call to action for India’s tech builders. Whether you’re setting up an offline assistant in Marathi or automating lights with vision-based triggers, your home can now be your AI lab.

We’d love to see what you build. Share your projects, scripts, or improvements with us—because the real power of local AI comes from community innovation.

🛠️ TechieBano.Com | Smart Gear. Smarter Minds.

2A

Agentic AI Home Assistants: The Future of Smart Living

by with No Comment AI & ML Tech

Agentic AI Home Assistants are redefining how we interact with technology. These systems don’t just respond—they think, plan, and take actions autonomously, giving you a smarter and stress-free home environment.

Unlike traditional assistants like Alexa or Google Assistant, these new-age agents act without waiting for commands. That’s right—your devices can now predict your needs, solve problems, and carry out tasks on their own.

What if your tech didn’t just follow commands, but actually thought ahead?

That’s the promise of Agentic AI—a new wave of intelligent systems that don’t wait for your input. They plan, decide, and act on your behalf. Let’s explore 5 real-world platforms that are already putting this future in your hands.

🔸 1. Rabbit R1 – Your Pocket-Sized Taskmaster

A tiny AI device that connects with your apps and carries out tasks automatically.
Why it’s smart: Understands what needs to be done—no instructions required.

🔸 2. Humane AI Pin – Wearable Assistant

It clips to your shirt and talks to you like a mini assistant.
Why it’s smart: Offers suggestions and takes action without wake words.

🔸 3. Auto-GPT / BabyAGI – DIY Smart Agents

For techies and tinkerers: AI agents that plan goals and complete tasks solo.
Why it’s smart: Sets its own steps and solves problems autonomously.

🔸 4. Samsung SmartThings Energy – Smarter Power Use

Optimizes your energy consumption at home.
Why it’s smart: Learns your usage patterns and cuts waste on its own.

🔸 5. TP-Link Deco AI Mesh – Self-Adjusting Wi-Fi

No more slow zones. It adapts your network in real time.
Why it’s smart: Switches channels, balances devices automatically.

⚙️ Also Catching Up…

  • Google Home + Bard
  • Alexa Smart Home Routines
  • Home Assistant with GPT

These systems are on their way to becoming fully autonomous, but they still rely on partial human input.

Benefits of Using Agentic AI Home Assistants

  • Eco-Friendly – Minimizes unnecessary power consumption
  • True Automation – Less micromanagement
  • Efficiency – Saves energy and bandwidth
  • Proactive Safety – Takes protective actions automatically
  • Time-Saving – Cuts repetitive tasks

🚀 Final Thought

Agentic AI is quietly taking over your home—not with sci-fi robots, but with smarter routers, plugs, and apps. You won’t notice them working. But you’ll definitely feel the difference.

Want more of this? Stay tuned to TechieBano—where we decode the future in simple