###### 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. Smart rural; IoT; sensors; ARIMA; SARIMA; teletraffic; precision agriculture; WSN, LPWAN 2020 10 7702 10.3390/app10217702 26 August 2020 19 October 2020 2020 30 October 2020 26 August 2020 19 October 2020 2020 30 October 2020 26 August 2020 20 19 October 2020 20 30 October 2020 20 20 30 October  
The study of these issues gave rise to the creation of the SCISEN research seedbed (Smart Cities & Sensor Network), which, with the participation of students and teachers, has made significant progress in the area of smart agriculture in Bogota, Colombia. One of the projects developed is based on the analysis of crops, such as potatoes. This study is in the central-eastern region of Colombia and seeks to establish optimal environmental and climatic conditions, soil characteristics, and other variables. Using a set of technologies integrated into the concept of Smart Agriculture, it seeks to establish the most optimal way to work with telecommunications networks, traditional wireless, and LPWAN networks (low power wide area network). Also, together with software applications and other devices, such as sensors, development cards, etc., it seeks to contribute to the consolidation of agricultural productivity in the sector [2]. Also, it was considered as antecedent to this research the importance that, at a global level, the application of smart agriculture in rural sectors has taken to improve productivity and strengthen food security in several countries of the world. The processes of technology transfer to the agricultural sector, generally associated with terms such as smart agriculture and/or smart farming, are seen by various government entities, such as the Food and Agriculture Organization (FAO), as a key factor to effectively address the future trends [2]. There is a need for optimized and more environmentally sustainable agriculture to support the growth of the world population, avoid the harmful effects of climate change, and preserve water and natural resources. Additionally, the IoT becomes an integrating and essential element for work in smart agriculture since it has important projections and applications in the immediate future. First of all, the agricultural sector has to be continuously monitored and controlled, which generates a large amount of data, for example, relevant environmental parameters for proper plant growth in a crop, which must effectively be collected, transferred, processed, and stored. In most cases, the deployment of data networks that generate connectivity in the field allows the exchange of information between nodes of an IoT architecture, and there the use of energy sources (for example, solar energy) to provide feeding to this scheme is mandatory.