---
title: "RNN implemention using Jupyter notebook and a Wiznet product, WIZnet IoT Shield for Cat.M1"
url: "https://maker.wiznet.io/luca__________/projects/jupyter-notebook-and-a-wiznet-product-rnn%2Clstm/"
markdown_url: "https://maker.wiznet.io/luca__________/projects/jupyter-notebook-and-a-wiznet-product-rnn%2Clstm/md"
type: "UCC: User Created Content"
author: "이해성"
author_url: "https://github.com/leehaesung/SQLite3_with_LTE_CatM1"
editor: "WIZnet"
editor_url: "https://maker.wiznet.io/"
original_author: "이해성"
original_url: "https://github.com/leehaesung/SQLite3_with_LTE_CatM1"
published: "2023-08-04"
language: "en"
likes: 0
views: 409
comments: 0
source: "WIZnet Makers (https://maker.wiznet.io/)"
---

# RNN implemention using Jupyter notebook and a Wiznet product, WIZnet IoT Shield for Cat.M1

> Jupyter notebook and a Wiznet product (RNN,LSTM)

Original author: 이해성 (source: https://github.com/leehaesung/SQLite3_with_LTE_CatM1)

## Article

## WIZnet IoT Shield for Arm Mbed

Motivation :

Since beekeeping (honey harvesting) travels around the country, there are many shaded areas where WiFi, LoRa/LoRaWan, and SigFox are not available. So, if you use the SKT LTE Cat.M1 IoT communication module, you can not only communicate anywhere in Korea, but also process the position (GPS) coordinates of the beehive, temperature, humidity, bee voice, and video image (small video).

SKT LTE Cat.M1 is a BG96 IoT module embedded WIZnet board and a digital thermo sensor measure the temperature and It transmits to the LTE station, switchboard, and application server. MQTT protocol's role are collecting temperature data and transmittance ,

store in SQL, CSV file extract, and data analysis(RNN, LSTM) DEEP Learning implemented in Jupyter notebook

HW (Pinout, Layout, Schematic, Gerber, BOM): [https://github.com/leehaesung/SQLite3_with_LTE_CatM1](https://l.facebook.com/l.php?u=https%3A%2F%2Fgithub.com%2Fleehaesung%2FSQLite3_with_LTE_CatM1&h=AT0pH9Oxg5lfVqXiLqFEpmS2uE0JFj5lDLCOTu5jfBoGAOuEX-oCnOQOseQW6tz0x-H0YJF4cDkcOAOGQS_yowVL6cGPSOA1FZ14k7FatQ1IoSym5hVCo_ty87IDnhgPnTAQgc5E3kUC&__tn__=-UK-R&c[0]=AT22O6qde69iHp0QwhvMbwuMLpvHBNQ8KXJuf2JS-jBn8roQfbann8ASvOPeKJspu1-NqYfblwVXXgk-EEzzK8Ue0fW_8_K1RZgoLv-ivyEbVNlO9eX6TDviJx5XTA0ese2OwK7HQYDhIq3sDADpQAQ0QL-dYxuanP-xYA2eURAzevueDoCAkSd55YYepDwmj-ap1cP7odaiUmySYhqlXdiFdhWUBYcZd9uLyUOv9nCsBH9Z)

**Source Code: **

```plaintext
Jupyter notebook(RNN) : https://nbviewer.jupyter.org/.../SQLite3_with_LTE_CatM1...
Jupyter notebook(LSTM,RNN) : https://nbviewer.jupyter.org/.../SQLite3_with_LTE_CatM1...
Arduino code : https://github.com/.../f_WIoT-QC01_Arduino_MQTT_SEND_JSON...

Contributors : 
Eric Jung(FW, H/W), Stephen Haesung Lee(펌웨어일부 수정, 시계열분석, RNN, LSTM, SQL, Python, Jupyter)

LTE Cat.M1 IoT payment list:
 https://www.sktiot.com/.../paymentSystem/paymentSystemCatM1
```

**Conclusion: When LTE IoT and deep learning are applied to beehives, honey production prediction, honey quality improvement, frost prevention in winter, convenient camera monitoring, and beekeeping farm productivity are expected to have a ripple effect. This is still an unfinished project. I would like to thank Kitae Park, general manager of G.camp, Seoul Business Agency for providing a development board test site and free IoT development training.**

![](https://github.com/Wiznet/wiznet-iot-shield-mbed-kr/raw/master/docs/imgs/hw/wiot-shield-qc01-nucleo-l476rg.png)

![image01](https://raw.githubusercontent.com/leehaesung/SQLite3_with_LTE_CatM1/master/01_Images/01_Setting.png)

---

Source: https://maker.wiznet.io/luca__________/projects/jupyter-notebook-and-a-wiznet-product-rnn%2Clstm/