Network Traffic Modeling in a Wi-Fi System with Intelligent Soil Moisture Sensors (WSN) Using IoT Applications for Potato Crops and ARIMA and SARIMA Time Series

Abstract

This article presents the results obtained by analyzing the data traffic that originated in a system with intelligent soil moisture sensors (Wireless Sensor Network—WSN) that transmit through a wireless network. This study sought to integrate smart agriculture and IoT (Internet of Things) applications in potato crops in various rural settings. Using these measurements, the data analysis was performed through the ARIMA (autoregressive integrated moving average model) and SARIMA (seasonal autoregressive integrated moving average model) time series following the Box–Jenkins methodology. GRETL (Gnu Regression, Econometrics and Time-series Library) free software was used to generate a teletraffic behavior prediction model in a larger-scale implementation. The main objective was the creation of a model that allows an analysis and simulation about the behavior of the main performance parameters that a medium-scale WSN system would have for the monitoring of a crop. Thanks to this analysis, it will be possible to determine the technical characteristics that a sensor deployment should have in a specific area and for a specific crop.

Forecasting COVID-19 cases for Top-3 countries of Southeast Asian Nation

“…Furthermore, several researchers have compared ARIMA and SARIMA Models. The results show that the SARIMA Model is better than the ARIMA Model (Rivero et al, 2020) and . In 2021, we have studied to estimate the number of COVID-19 new cases in Indonesia applying two mathematical models ARIMA and SARIMA (Suryani & Binarto, 2021).…”

Determination of Crop Soil Quality for Stevia rebaudiana Bertoni Morita II Using a Fuzzy Logic Model and a Wireless Sensor Network

“…Monitoring systems, often referred to as internet of things (IoT) or precision agriculture systems, have emerged as a common solution for collecting data on various variables of interest. These systems enable the gathering of environmental variables [13][14][15][16][17], soil parameters [18][19][20][21][22], and water parameters [23]. Typically, such systems comprise electronic sensors designed to measure specific variables, along with microcontrollers or interconnected microcontrollers that interpret the sensor data and transmit it wirelessly as a wireless sensor network (WSN).…”

“…To facilitate data analysis, these monitoring systems often include a graphical interface that allows users to access and visualize the collected data. Moreover, the interface may support data export for further processing and analysis [13,14,16,17,[19][20][21][22][23].…”

“…These microcontrollers are often integrated into embedded development boards such as node microcontroller units (NodeMCUs) and TTGO boards made by LILYGO. Their popularity stems from their user-friendly nature and support for the Institute of Electrical and Electronics Engineers (IEEE) 802.11 protocol, also known as WIFI, enabling wireless communication and internet access when connected to compatible networks [14,15,17,18,22].…”

“…Each protocol offers distinct advantages, such as range, data rate, bandwidth, and module cost [22,24]. In the literature, LoRa and IEEE 802.11 have been frequently mentioned and used.…”