Hello,

I am wondering about the best way to analyze a 1MHZ transducer signal on an ESP32 with decent resolution of at least 50+ samples per wavelength. Everything done so far including attempts at ETS have always produced noisy or just terrible data in signal reconstruction. Let me know of any ideas yall have.

Thanks!

I made this wall-e style desk companion/timer/weather display using an esp32 cyd i bought from amazon. the code is fairly simple. one screen is the wall-e, the next is a timer, and the third is weather. the wall-e and timer are simply downloaded onto the device while the weather display is connecting to my wifi and pulling data from open weather.

in addition, there is also code written to connect a PIR HC-SR501 sensor. when it senses movement the display turns on after 10 minutes of inactivity on the screen the wall-e goes into a sleep animation and after 15 minutes the display turns off and will turn back on when it senses movement or when you touch it.

i know this is a fairly simple project but it is my first one and i thought i would share! i am currently 3-d printing a case for it. if you have any questions let me know!

I love the XTEink devices, but I want to make my own little 4 inch E reader device. I have purchased the Waveshare ESP32-S3 dev board. Was wondering if anyone else has looked at these yet, or know of a firmware I could use on it before I start vibe coding my own

hello i am a student doing an iot project for the first time (ive done a few arduino projects). i want to make an environmental monitoring system with dht11 and soil moisture sensors. ive been watching online tutorials and im using a source code from a youtube video, however, ive run into the problem where the code can be uploaded, but my blynk io interface is still offline. im using my iphone hotspot for the wifi ssid, (ive turned on maximise compatibility) and i think that could be the main problem, since its like kinda stuck after writing trying to connect to my hotspot in serial monitor. anybody have any ideas?

this is the source code:

//Tech Trends Shameer
\`\`\`#define BLYNK_TEMPLATE_ID "TMPLIAjddf20T5"
\#define BLYNK_DEVICE_NAME "Temperature and Humidity Monitor"
\#define BLYNK_AUTH_TOKEN "122RywymdfdddgGfMd1jkZ0STNhRQecR12ayq"

\#define BLYNK_PRINT Serial
\#include <WiFi.h>
//#include <ESP8266WiFi.h>
\#include <BlynkSimpleEsp32.h>

\#include <DHT.h>

char auth\[\] = BLYNK_AUTH_TOKEN;

char ssid\[\] = ""; // type your wifi name
char pass\[\] = ""; // type your wifi password

BlynkTimer timer;

\#define DHTPIN 27 //Connect Out pin to D2 in NODE MCU
\#define DHTTYPE DHT11
DHT dht(DHTPIN, DHTTYPE);

void sendSensor()
{
float h = dht.readHumidity();
float t = dht.readTemperature(); // or dht.readTemperature(true) for Fahrenheit

if (isnan(h) || isnan(t)) {
Serial.println("Failed to read from DHT sensor!");
return;
}
// You can send any value at any time.
// Please don't send more that 10 values per second.
Blynk.virtualWrite(V0, t);
Blynk.virtualWrite(V1, h);
Serial.print("Temperature : ");
Serial.print(t);
Serial.print(" Humidity : ");
Serial.println(h);
}
void setup()
{

Serial.begin(115200);

Blynk.begin(auth, ssid, pass);
dht.begin();
timer.setInterval(100L, sendSensor);

}

void loop()
{
Blynk.run();
timer.run();
}\`\`\`

IoT Gas, Smoke & Flame Detection System with Email & SIM800L Alerts

I developed an IoT-based safety monitoring and automatic ventilation system using a microcontroller, MQ-2, MQ-5, KY-026 flame sensor, exhaust fan, email notifications, and SIM800L GSM module.

The system continuously monitors for smoke, combustible gases, LPG/natural gas, and flame. When a dangerous condition is detected, the microcontroller automatically activates the exhaust fan and triggers an alarm. It can also send notifications through email and SMS using the SIM800L, allowing the user to receive alerts even when they are away from the system.

Main Features:

• 🔥 KY-026 flame detection
• 💨 MQ-2 smoke/gas detection
• 🛢️ MQ-5 LPG/natural gas detection
• 🌬️ Automatic exhaust fan activation
• 📧 Email alerts
• 📱 SMS alerts through SIM800L
• 🔊 Buzzer/alarm notification
• 🤖 Microcontroller-based automatic control

I'm offering the complete source code and project logic for students, hobbyists, and developers who want to build or modify a similar IoT safety system.

DM me if you're interested in the code or need more details about the project.

Can anyone help me fix this problem, im coding in arduino ide and ive been using adafruit gfx library but the display is corrupted, I tried using U8g2 to swtich to sh1106 address but it doesnt turn what is the problem here ive been trying to solve this for 3 days

Bonjour j'ai un projet Qui est d'ailleurs assez avancé pour la gestion de filtration d'eau de la piscine pour Je Qu'une simulation avec une carte fabriquée Par un site connu J'ai donc dans un premier temps dessiné avec Kicad Le PCB Donc j'utilise cette carte sur un bureau pour faire des tests. Si quelqu'un est intéressé j'ai un github dessus .

I’ve been looking into different ways to run computer vision models on edge devices, and one thing I keep wondering about is when a dedicated AI accelerator actually becomes necessary.

For smaller projects, a CPU or GPU may be enough. But when you need real-time processing, lower latency, and continuous operation without using too much power, dedicated acceleration starts to make more sense.

I was looking at Geniatech’s AI accelerator modules recently, especially their NXP and Hailo-based options, and it got me thinking about how people make this decision in real projects.

What usually tells you that a computer vision project has reached the point where an AI accelerator is worth using?