Build an Android or iOS app for your hardware with no coding!
Smart Garden is a plant environmental monitoring system.
A project that speaks on behalf of mother nature. It is real time air quality monitoring device.
Chunchunmaru is an Arduino UNO-based robot which can carry heavy loads (100kg-200kg) from one location to another.
Octopod, a uniquely shaped full automation system that allows you to monitor your industry and keep security with AI and smart RFID locks.
Controlling water and heat of a plantation, using real data as temperature, relative air humidity, and soil moisture.
saving water smartly.
Monitor the surrounding dust and large particle (>0.5µm) for long time using Blynk IOT and plot the data for further research.
A system that warns for unexpected rains to help out your garden. The system displays real time values on mobile.
A cube with all the necessary sensors, suitable for a wide range of applications like agriculture. Know the land beneath you!
Save time by knowing whether the Faculty is in his chamber or not.
Every time a movement is detected by the sensor, a message is sent to a smartphone anywhere in the world!
We show how to connect Pico to WiFi while maintaining low power and running it directly on AAA batteries.
Control temperature, humidity, CO2, and light with an automated open-source mushroom fruiting chamber using ESP32 and Blynk 2.0.
An IoT smart mailbox for securely receiving parcels and getting notification on app without being present at home.
Monitor your blood oxygen level with this ESP32 based Oximeter. This Oximeter costs less than 10$.
Monitor weather and security remotely with Blynk and the CC32000 LaunchPad!
Know when your clothes are dry
Make your own IoT based home/office security system using the Nodemcu ESP8266 Wifi module, PIR Sensor and Blynk application.
Automatic and smart care of plants by proper watering and their monitoring.
Save water, save energy and monitor water consumption with a smart faucet.
Collect environmental factors and culture amount while producing yogurt. Then, run a neural network model via Blynk to predict its texture.
How can scientists model and predict the formation of sink holes using IoT?
Collecting multiple data from multiple sensors connected to the same 1-wire bus and monitoring them from the internet with Blynk.
