The number of technical solutions to remotely monitoring elderly citizens and detecting hazard situations has been increasing in the last few years. These solutions have dual purposes: to provide a feeling of safety to the elderly and to inform their relatives about potential risky situations, such as falls, forgotten medication, and other unexpected deviations from daily routine. Most of these solutions are based on IoT (Internet of Things) and dedicated sensors that need to be installed at the elderly’s houses, hampering mass adoption. This justifies the search for non-invasive technical alternatives with smooth integration that relying only on existent devices, without the need for any additional installations. Therefore, this paper presents the SecurHome TV ecosystem, a technical solution based on the elderly’s interactions with their TV sets—one of the most used devices in their daily lives—acting as a non-invasive sensor enabling one to detect potential hazardous situations through an elaborated warning algorithm. Thus, this paper describes in detail the SecurHome TV ecosystem, with special emphasis on the warning algorithm, and reports on its validation process. We conclude that notwithstanding some constraints while setting the user’s pattern, either upon the cold start of the application or after an innocuous change in the user’s TV routine, the algorithm detects most hazardous situations contributing to monitor elderly well-being at home.

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In many countries, the number of elderly people has grown due to the increase in the life expectancy of the population, many of whom currently live alone and are prone to having accidents that they cannot report, especially if they are immobilized. For this reason, we have developed a non-intrusive IoT device, which, through multiple integrated sensors, collects information on habitual user behavior patterns and uses it to generate unusual behavior rules. These rules are used by our SecurHome system to send alert messages to the dependent person's family members or caregivers if their behavior changes abruptly over the course of their daily life. This document describes in detail the design and development of the SecurHome system.

There is an error in reference 12, which will be corrected. The original article has been corrected.

People living with deafness or hearing impairment have limited access to information broadcast live on television. Live closed captioning is a currently active area of study; to our knowledge, there is no system developed thus far that produces high-quality captioning results without using scripts or human interaction. This paper presents a comparative analysis of the quality of captions generated for four Spanish news programs by two captioning systems: a semiautomatic system based on respeaking (system currently used by a Spanish TV station) and an automatic system without human interaction proposed and developed by the authors. The analysis is conducted by measuring and comparing the accuracy, latency and speed of the captions generated by both captioning systems. The captions generated by the system presented higher quality considering the accuracy in terms of Word Error Rate (WER between 3.76 and 7.29%) and latency of the captions (approximately 4 s) at an acceptable speed to access the information. We contribute a first study focused on the development and analysis of an automatic captioning system without human intervention with promising quality results. These results reinforce the importance of continuing to study these automatic systems.