Currently, many applications have emerged from the implementation of software development and hardware use, known as the Internet of things. One of the most important application areas of this type of technology is in health care. Various applications arise daily in order to improve the quality of life and to promote an improvement in the treatments of patients at home that suffer from different pathologies. That is why there has emerged a line of work of great interest, focused on the study and analysis of daily life activities, on the use of different data analysis techniques to identify and to help manage this type of patient. This article shows the result of the systematic review of the literature on the use of the Clustering method, which is one of the most used techniques in the analysis of unsupervised data applied to activities of daily living, as well as the description of variables of high importance as a year of publication, type of article, most used algorithms, types of dataset used, and metrics implemented. These data will allow the reader to locate the recent results of the application of this technique to a particular area of knowledge.

The Assisted Living Environments Research Area–AAL (Ambient Assisted Living), focuses on generating innovative technology, products, and services to assist, medical care and rehabilitation to older adults, to increase the time in which these people can live. independently, whether they suffer from neurodegenerative diseases or some disability. This important area is responsible for the development of activity recognition systems—ARS (Activity Recognition Systems), which is a valuable tool when it comes to identifying the type of activity carried out by older adults, to provide them with assistance. that allows you to carry out your daily activities with complete normality. This article aims to show the review of the literature and the evolution of the different techniques for processing this type of data from supervised, unsupervised, ensembled learning, deep learning, reinforcement learning, transfer learning, and metaheuristics approach applied to this sector of science. health, showing the metrics of recent experiments for researchers in this area of knowledge. As a result of this article, it can be identified that models based on reinforcement or transfer learning constitute a good line of work for the processing and analysis of human recognition activities.

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This article contains methods, results, and analysis agreed for the development of an application based on the internet of things and making use of machine learning techniques that serves as a support for the identification of the saline wedge in the Magdalena River estuary, Colombia. As a result of this investigation, the process of identifying the most suitable telecommunications architecture to be installed in the estuary is shown, as well as the characteristics of the software developed called SISME (Estuary Monitoring System), and the results obtained after the implementation of prediction techniques based on time series. This implementation supports the maritime security of the port of Barranquilla since it can support decision-making related to the estuary. This research is the result of the project “Implementation of a Wireless System of Temperature, Conductivity and Pressure Sensors to support the identification of the saline wedge and its impact on the maritime safety of the Magdalena River estuary”.

The loss of reproductive efficiency of animals and cattle rustling have become one of the main concerns of farmers. The decrease in reproductive efficiency is mainly due to the low percentage in heat detection. Reproductive efficiency is commonly measured by the interval between births, which affects the daily milk production of the cow during its productive life and the income associated with the sale of milk from its production, conditioning the profitability of the farmers. The zeal for its part consists of the theft of bovine cattle that usually is used for its commercialization, bringing considerable losses. According to figures from the Observatory of Human Rights and International Humanitarian Law of the Fundacion Colombia Ganadera, Fundagán, only during 2014 there were 164 cases of cattle rustling, resulting in the loss of 3,798 cattle throughout the country, which represents a loss for the producers of 15 billion of Colombian money. This project proposes the development of a technological platform that combines hardware, software and communications systems of the latest technology and with open standards to provide an economic and reliable solution to the Colombian and Latin American livestock industry. In Colombia, there is a history of products and prototypes that have been developed to alleviate this problem, no platforms of similar benefits have been found that are accessible to farmers in the country. In this article, the different stages developed to obtain a validated prototype with the beneficiary entity and their respective results are socialized.