Arduino's edge-controlled remote monitoring board can be placed anywhere and is suitable for precision farming, smart farming, and other applications that require remote smart control. Power can be supplied via solar panels or DC input.

Applications using the edge control board can be remotely controlled via the Arduino Cloud (or a third-party service) using connection options appropriate for the location. Edge control features built-in Bluetooth™, and by adding any of the MKR boards, its connectivity can be extended with 2G/3G/CatM1/NB-IoT modems, LoRa™, Sigfox and Wi-Fi. Edge-controlled remote monitoring can connect sensors and actuate actuators such as latching valves (common in agriculture). It has the ability to monitor the entire process in real time, thereby reducing production-related risks.

The remote monitoring board is suitable for smart agriculture, and sensors can collect data such as weather conditions, soil quality, and crop growth in real time. Once sent to the Arduino cloud, the data value chain becomes valuable analytics that support business processes at every level (eg, crop yield, equipment efficiency, employee performance, etc.). Remote monitoring panels can improve crop quality and reduce manpower/errors by automating processes such as irrigation, fertilization or pest control.

feature

input Output

6x edge sensitive wakeup pins

16x hydrostatic watermark sensor inputs

8x 0 V to 5 V analog inputs

4x 4 mA to 20 mA inputs

8x latching relay command outputs with driver

8x latching relay command outputs, no driver

Four 60 V/2.5 A Galvanically Isolated Solid State Relays (SSRs)

6x 18-pin plug-in terminal block connectors

memory

1 MB onboard flash

2 MB onboard QSPI flash

SD card slot

Operating Temperature: -40°C to +85°C (-40°F to +185°F)

processor

64 MHz Arm? Cortex?-M4F (with FPU)

Connectivity (*requires Arduino MKR board)

Bluetooth

Wi-Fi*_3G*_Narrowband IoT*_LoRaWAN?*_Power

Low power consumption (up to 34 months with 12 V/5 Ah battery)

12 V acid/lead battery power via solar panel charging

Lithium battery backup

Weight: 67 grams

Dimensions: 86mm x 104mm

benefit

Precision Agriculture and Process Automation

Increase yield and reduce production risk

real-time and historical data

Monitor environmental conditions

Can be powered by solar panels

Easy installation

Easily connect sensors/devices

Operates at high and low temperatures

Choice of connection type

Support for TensorFlow Lite micro for tiny machine learning applications

application

Intensive farming

Smart Agriculture

Smart Irrigation System

automated greenhouse

Hydroponics/Aquaponics

mushroom cultivation