###### Abstract
In Colombia, an effort has been made to start the application of the concepts of smart agriculture and precision agriculture in coffee [2], sugar cane [3], and strawberry [4] crops, among other crops, in different regions (Llanos orientales, coffee axis, Valle del Cauca). However, one of the main difficulties is the lack of technological coverage and connectivity to the internet to be able to transmit the data acquired in rural sectors to the municipal capitals, where there are the points that are part of the Live Digital Plan implemented by the Ministry of ICT (Information and communication technologies) in Colombia and other government institutions in agreement with the National Development Plan 2010-2014. This void, which the government has not been able to solve in Colombia over several years and which currently has been evidenced more strongly by the effects of the COVID-19 pandemic, demonstrates the connectivity problems in a large percentage of rural Colombian territory, and constitutes the origin of the research that is presented in this document. Specifically, a prototype of a network of nine smart soil moisture sensors, FC28, was implemented on the ESP8266 NodeMCU development platform that transmits under the 802.11n protocol (Wi-Fi) in the 2.4 GHz band. These signals were received by a LINKSYS WAP300N reference router that centralized the signals from the ESP8266 modules previously configured in station mode with addresses assigned by the router's DHCP (Dynamic Host Configuration Protocol) service. The assigned addresses were configured in the range between 192.168.0.10/24 to 192.168.0.30/24. A LAN (Local area network) was implemented with a gateway that was configured at address 192.168.0.1/24. This wireless LAN network, implemented in the building of the Faculty of Engineering in basement 3 where the facilities of the LIDER research group are located, has a coverage of approximately 90 m around the point where the main router is located. However, the tests were conducted with the sensors located at approximately 50 m around the router. Likewise, the computer where the Wireshark software was installed was connected to this same LAN network, which was used as a network sniffer to capture, filter, and analyze data packets sent in the wireless network, as described in [5]. With this, it was proposed to carry out an analysis of data traffic in order to model and characterize the performance of the wireless channel to predict its behavior and apply it in a larger-scale implementation; more specifically, in a smart agriculture project that benefits the cultivation, for example, of potatoes in Colombia and Spain [6], where this case study was conducted. Not limited only to potatoes, other irrigated crops such as vegetables or beets can also benefit from the system. The Linksys WAP300N router has a transmission capacity of up to 300 Mbps in the 2.4 GHz and 5.0 GHz bands. However, this speed by standards is reduced by headers, acknowledgments (in certain protocols), speed of the interfaces' host, processing capacities and memory, etc. Throughput for the interfaces can vary a lot. However, in this case it was not relevant, considering that the rest of the link limited the channel speed. The typical throughput for the signals transmitted in the study case was 80 Mbps. The antennas of the ESP8266 platforms were also limited by the standard used and offered a typical throughput of approximately 60 Mbps. Thus, the maximum values between points of the link, considering the speed and throughput specified by the standards, are shown in the Figure 1.  
In this article, the use of time series is proposed because the sequences of the samples of the observed variable were typically taken in successive instances of time and evenly spaced. To achieve this, 200 samples were taken from the humidity sensor that were read by a wireless device, the ESP8266, which transmitted them to a WiFi device.