# Design of a low-cost smart irrigation system based on NB-IOT for agriculture

## TL;DR

A low-cost smart irrigation system using NB-IoT technology is designed to improve water and energy efficiency in agriculture.

## Contribution

The system introduces a three-layer architecture and achieves cost reduction while maintaining high performance and accuracy.

## Key findings

- The system's waveform stability met standards with a carrier frequency offset of −1.50 MHz and peak transmit power of −20 dBm.
- The optimal communication distance was 1600 meters with a packet loss rate of ≤12.8%.
- The system's irrigation error was 1.76 (simulation) and 1.74 (field test), meeting industrial standards.

## Abstract

In the process of agricultural modernization, irrigation has the potential to promote utility of water and energy. It is essential to optimal use of resource sustainability. However, smart irrigation is faced with high running cost problems, which cannot meet demand of modern agricultural development. In this study, a low-cost smart irrigation system based on NB-IoT applied to agriculture is proposed. The system introduces three-layer module architecture to improve efficiency. And the experiment introduces multiple methods such as waveform stability test and communication distance test to optimize performance. For NB-IoT stability testing. during operation, the waveform’s carrier frequency offset reached −1.50 MHz (within the standard allowable range) and remained stable, with a peak transmit power of −20 dBm. For communication performance, the optimal communication distance of the system is within 1600 meters, with an ideal packet loss rate of ≤10% (12.8% at 1600 meters). For precision, the average irrigation error of the system is 1.76 (simulation) and 1.74 (field test), which meets industrial accuracy standards. And the total hardware cost of the system is 17.5–29.3% lower than other similar low-cost systems. The proposed NB-IoT-based smart irrigation system enhances practicality, reduces costs, and maintains high accuracy. It provides new insights for advancing smart agriculture and resource sustainability.