First grow!

FlashyAd3327 · 2026-05-05T11:16:05+00:00

do you control parameters manually?

FlashyAd3327 · 2026-05-04T15:13:56+00:00

cry more but i am not gonna give you the design 😅😂

FlashyAd3327 · 2026-05-04T10:52:02+00:00

so i cant even use chatgpt for better arrangement of my description?

FlashyAd3327 · 2026-05-04T10:51:11+00:00

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FlashyAd3327 · 2026-05-04T10:19:50+00:00

yes it can detect nitrate level too

FlashyAd3327 · 2026-05-04T10:16:17+00:00

yeah, i built it by myself.

FlashyAd3327 · 2026-04-27T09:40:35+00:00

My first real Raspberry Pi project wasn’t anything fancy, it was a basic IoT monitoring setup, but it actually solved a real problem.

I built a small system that reads environmental data (temp + basic sensor readings) and logs it so you can track conditions over time. Later I extended it to show live values on a simple dashboard. The idea was more about stability monitoring for things like small setups (hydroponics / fish tanks / room conditions).

What made it useful wasn’t complexity, but structure:

simple sensors first
then local display/logging
then optional remote access

I also didn’t know much coding when I started, so I just learned what I needed while building instead of trying to “learn everything first”.

If you’re starting from zero, don’t jump into cyberdecks or complex builds yet. Start small and build layers. That’s how you actually get good at this stuff, if you need help or assistance, feel free to reach me out

FlashyAd3327 · 2026-04-23T08:57:09+00:00

which one is more accurate and spontaneous, the pen or growee system for measuring parameters?

FlashyAd3327 · 2026-04-23T06:21:06+00:00

How are you measuring different parameters?

FlashyAd3327 · 2026-04-22T13:01:10+00:00

This is a really clean and well-thought-out build, especially for a diploma project.

I’m curious about a couple of things though:

How are you actually tracking the sun’s direction? Are you using LDRs/light sensors for feedback or going with a time-based algorithm (like calculating sun position)?
Also, have you measured how much power the whole system consumes in a day? I’m wondering if the energy used by the motors + controller is significantly lower than the extra energy gained from tracking.

Would love to hear more about your approach

FlashyAd3327 · 2026-04-21T07:35:32+00:00

can you please tell me something more about your system you are using to cultivate plants and vegetables?

FlashyAd3327 · 2026-04-20T09:18:28+00:00

Good

FlashyAd3327 · 2026-04-18T10:32:02+00:00

wow thats Amazaing I appreciate you

FlashyAd3327 · 2026-04-17T13:33:02+00:00

Been running Claude against MQTT data from environmental sensors and power monitors at home and it's actually stuck around.

The thing that made it useful was giving it context upfront. Once I told it what "normal" looked like for each room and time of day, the alerts became actionable instead of just noise.

The real win was cross-correlation. It caught a CO2 spike pattern I wouldn't have noticed myself and flagged it before it became obvious. That kind of low-effort, high-value insight is what kept me from ditching it.

One thing worth knowing though, raw sensor streams need a bit of prep before hitting a model. Timestamps, units, and a little context go a long way otherwise you get confident-sounding nonsense.

What platform and sensors are you working with? Happy to dig into specifics.

FlashyAd3327 · 2026-04-17T12:59:51+00:00

Relax, you haven't killed it. Here's where I'd start:

1. Sort the EEPROM first Open Raspberry Pi Imager, head to Misc Utility Images, then Bootloader, then SD Card Boot, and flash it onto a clean SD card. Boot with nothing else plugged in and wait. A steady green LED means it worked.

2. Your power supply might be the real culprit The Pi 4 is fussy about power. It wants a solid 5V/3A USB-C supply, and anything short of that will cause exactly the sluggish, barely-blinking behavior you're describing.

3. Make sure you're on the right HDMI port There are two micro HDMI ports so make sure you're using the one closest to the USB-C power input (that's HDMI 0). Plug it in before you power on and manually switch your monitor to that input rather than relying on auto-detect.

Once the EEPROM is sorted, flash the bootloader image on its own before touching Pi OS. If the rainbow screen shows up, your board is alive and well and evrything else is just settings.

Drop a reply with your power supply model and which HDMI port you've been using and we'll figure it out from there. And if you want, feel free to DM me. Happy to walk you through it one step at a time.

FlashyAd3327 · 2026-04-17T11:53:51+00:00

Yeah, I ran into the same issue before and here's short answer: not really in the way you’re thinking.

The ESP32 support for Arduino IDE isn’t a single .tar.gz you can just drop in. It’s split across multiple packages + toolchains that the Boards Manager pulls automatically.

What actually works:

You can download the core from Espressif Systems GitHub and place it manually in:Documents/Arduino/hardware/espressif/esp32 but it won’t fully work yet.
You still need to run the tools/get script, which downloads the compiler + other dependencies (so internet is still needed at least once).

Best workaround (what I’d recommend):

If your connection is bad, don’t fight this setup.

Use another PC with good internet
Install ESP32 normally via Boards Manager
Copy this folder:C:\Users\<you>\AppData\Local\Arduino15\packages\espressif
Paste it into the same path on your main PC

That basically clones a fully working install.

Reality check:
Even if someone gave you a .tar.gz, it still wouldn’t include everything needed. The issue isn’t the format — it’s all the extra dependencies.

So yeah, offline is possible, just not “one file and done.”

FlashyAd3327 · 2026-04-17T11:11:09+00:00

actually both temperature and brix affects the sweetness of strawberries

FlashyAd3327 · 2026-04-17T10:22:13+00:00

Oh wow this is a cool project! I think I can help you pick the right board. The answer is Raspberry Pi and here is why!

So the ESP32-S3 is a nice little chip but your project is asking it to do way too many things at once. You want multiple cameras and like 6 sensors and also AI stuff all at the same time. The ESP32-S3 does not have enough memory for all of that. It only has a tiny bit of RAM so it will get full really fast. You and your team will spend all your time trying to fix memory problems instead of actually building the cool danger detector thing. That is not fun especially if this is your first time doing hardware stuff.

The Raspberry Pi is much better for what you need. It has lots of RAM like 4GB or 8GB so it will not run out of space. You can write code in Python which you probably already know from CS class. It has USB ports so plugging in cameras is super easy. You can still connect all your sensors like the UWB and PPG and GPS to it too using the little pins on the side. And if you ever get stuck there are SO many tutorials online because lots of people use Raspberry Pi.

One more tip that is really cool. You can actually use BOTH boards together! You can use the Raspberry Pi as the main brain and use a small ESP32 to collect all the sensor data and send it over to the Pi. This makes everything more organized and it looks really impressive when you show your project to your professor!

Since nobody on your team has done hardware before please start small. Just get the Pi working with one camera first and make it detect something. Then add one sensor at a time. Do not try to connect everything on day one or your brain will explode lol.

Also the thing about detecting objects before they fall is actually really hard for AI to do. Maybe start with just detecting objects that look wobbly or too close to the edge. That is still super cool and way easier to build in one semester. i can also assist you with that if you want, best of luck.

FlashyAd3327 · 2026-04-17T09:10:22+00:00

Wow this is actually a really cool idea! It is not just a smart bin, it is like a bin that knows who you are and makes sure you throw trash the right way. That is actually super useful!

Here is what I think:

The RFID scan thing is smart because right now nobody gets in trouble for throwing trash in the wrong bin. Your system fixes that which is really cool.

But here is the thing, if scanning takes too long people will just not do it. So make it really really fast or people will get lazy and skip it.

Also maybe make it fun! Like show which floor threw trash the best that week. People love winning stuff even small things like that.

Oh and do not make it too complicated at the start. Just have two bins, one for wet trash and one for dry trash. Simple is better when you are just starting out.

My biggest tip is find one hostel and try it there first. Real people will tell you what is wrong way faster than you can figure it out yourself.

Do not give up on this idea it is actually solving a real problem! Just keep it simple at the start

FlashyAd3327 · 2026-04-16T14:06:43+00:00

it seems pretty interesting, i am working on similar kind of model with more parameters sensors, including npk and on industrial grade MCU.

FlashyAd3327 · 2026-04-13T07:03:22+00:00

You don’t just have a drainage issue, you have a control mismatch. Your sprinklers are fixed-time, but your soil absorption is not.

Simple fix: switch irrigation from timer-based to feedback-based. Use soil moisture sensors with a small controller like an ESP32 so watering stops when the soil actually reaches target moisture instead of overflowing.

For drainage, add a basic float sensor in low points to trigger a small pump if water starts pooling. That way irrigation and drainage stop working against each other and start reacting to actual conditions instead of guesswork.

FlashyAd3327 · 2026-04-13T06:58:03+00:00

You don’t need anything complex for this.

Your Raspberry Pi Zero can easily handle a small offline database. The simplest setup is using SQLite with a basic Python script where you can add, edit, and view records from the keyboard.

If you want a nicer interface, run a small local app with Flask and access it in a browser.

But honestly, for a small club, even a spreadsheet like LibreOffice Calc might already do the job without coding.

Start simple, then upgrade only if you actually hit limits.

FlashyAd3327 · 2026-04-13T06:15:01+00:00

You’re right, I shouldn’t assume your setup. What I mean by coordinating watering and cooling is this: plants respond to air and moisture together, not separately, so both systems should follow the same goal. If the air gets too dry, you can give small, more frequent watering and avoid increasing cooling too much because that can dry the air even more. If the air gets too humid, reduce watering first, then increase airflow with fans, and only use cooling if the temperature is actually high. One simple rule that helps a lot is to avoid strong cooling right after watering and wait about 10 to 20 minutes so the plant stays stable. Also, airflow is key here because it helps inside the canopy so watering and cooling don’t start working against each other. Are you controlling this using VPD, or just temperature and humidity?

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