ESP 32 and machine learning
ESP32 architecture supports onboard ML models. Predictive analysis based on the collected array of data sets through post- training sessions. Depending on the use case basic ML can be enabled for small data sets
Detailed overview of our capabilities using ESP32 IOT dashboard
- Integration of different sensor types – ESP32 can be used to integrate different types of sensors widely used in the IOT platform. Sensors are available in different protocols such as analog, digital, i2c, SPI, and serial. ESP32 comprises 18 ADC converter channels, 3 SPI interfaces, 3 UART interfaces, and 2 I2C interfaces and the architecture also supports different sensor libraries provided along with the sensors. So these types of sensors can be directly connected to the board and collect data from it.
- Smart wifi configuration – Using the smart wifi configuration, users can easily configure the ESP32 into the required network. A web page is provided to connect to their required Wi-Fi once they are connected to the hotspot created by ESP32 on startup.
- Direct data sending to the cloud – ESP32 supports internet connectivity with an integrated Wi-Fi module. Data collected from various sensors can be sent directly to the cloud without having a gateway and can act as a stand-alone device.
- BLE data reading and sending – This low-power system on a chip microcontroller is integrated with dual-mode Bluetooth. The inbuilt Bluetooth low energy (BLE) protocol enables a power-efficient method to collect data from the advertising Bluetooth beacons using the continuous scanning technique. It can also advertise data collected from the non-BLE sensors using the BLE protocol.
- Different protocols for data sending – It can integrate most of the protocols for data sending such as MQTT, HTTP, BLE, WiFi, etc. Using these protocols we can send data locally or to the cloud according to the customer choice.
- Over the air update – It provides the capability to update the firmware from anywhere if the internet facility is provided. This will enable updating to new firmware versions with improved features as well as add the additional customer requirements remotely once the module is deployed in the working environment.
- Basic machine learning – since the ML model currently supports a limited subset of operation.
Our ESP 32 IOT dashboard is suited for wireless remote monitoring applications in farm automation, Indoor air quality monitoring, Noncontact temperature monitoring, touchless attendance tracking, temperature & humidity, soil moisture, and other parameters such as ambient light & CO2 levels.