A conceptual and algebraically framework that did not exist up until then in its morphology, was developed. What is more, it is pioneer on its implementation in the area of Artificial Intelligence (AI) and it was started up in laboratory, on its structural aspects, as a fully operational model. At qualitative level, its greatest contribution to AI is applying the conversion or transduction of parameters obtained by ternary logic [1] (multi-valued systems) and associating them with an image. This image will be analysed by means of a residual artificial network ResNet34[2], [3] to warn us of an intrusion. The field of application of this framework includes everything from smartwatches, tablets, and PC’s to the home automation based on the KNX standard[4]. This framework proposes for AI, a reverse engineering, in such a way that drawing on common and revisable mathematical principles, which applied in a 2D graphical image to detect intrusion. Reverse engineering will be scrutinised the device’s security and privacy by using artificial intelligence in order to mitigate these lesions for the end users. Furthermore, the framework is postulated to meet the highest expectations of being an useful tool for society and human being aligned with «Opinion of the European Committee of the Regions – White Paper on Artificial Intelligence — A European approach to excellence and trust». Besides contributing to avoid the malpractice of generating black boxes [5] in the use of artificial intelligence[6], making it something incomprehensible. Confidence and clarification in technology is a short-, medium- and long-term goal to society do not be affected by the spurious technologies, which prejudice a good social CEDRO The Bible of AI ™ OpenScience • Authors' publicationsFramework based on parameterized images on ResNet to identify intrusions in smartwatches or other related devices 3development. «These technologies have extended the opportunities of freedom expression and social, civic and political mobilization. At the same time they arouse serious concerns»[7]. I. Framework 1.- Need to know There is a widespread availability of «intelligent» devices that all we have our disposal, from digital cameras, tablets to smartwatches. The problem occurs when the lack of knowledge of these electronic devices management extends to a large percentage of the population[8], thus ignoring the risks which might be entailed. Although it is true that an electronic device is intelligent because it interacts appropriately and autonomously, we cannot forget this theory: If something brings benefits and solutions in specific situations, it means something should know in advance what is occurring. It all comes down to a simple word: data. One of the most innovative electronic devices is smartwatch. Smartwatches have sensors which identify models or human behaviour patterns based on automatic learning techniques, the Bayes theorem, processing data and the method of K Nearest Neighbours [9]. These procedures raise a large volume of information with which we intent to meet the goal by specifying the results that are expected. These sensors are very useful for monitoring human activity: walking, cycling, running and walking up and down stairs [10]. The use of smartwatches may represent a serious threat to the safety of children and adolescents [11]. The most important safety failures of low-cost smartwatches happen in applications and in connections with servers which store data. The most popular brands of smartwatches used by minors are Carl Kids Watch, hellOO! Children’s Smart Watch, SMA-WATCH-M2 y GATOR Watch. The highest recurring problems we face are certain failures in the implementation of certifies for secure connections HTTPS [12] and information related to unencrypted electronic register [13]. Nevertheless, devices from popular manufacturers like Nokia [14], Samsung and Huawei[15], these kind of problems are not frequent because they use encrypted connections. In that regard, it is important to note the conditions that affect to the safety of smartwatches’ brands. In this way, when buying a smartwatch this information will be useful. Mainly, the criterion for choosing brands is knowing the number of sales: Samsung, Apple, Fitbit and Garmin. The Bible of AI ™ OpenScience • Authors' publicationsFramework based on parameterized images on ResNet to identify intrusions in smartwatches or other related devices 4SAMSUNG APPLE Image 1 Image credit: Security in Samsung and Apple devices by Adrián Hernández, 2021, Mangosta (https://mangosta.org/seguridad-en-los-dispositivos-samsung-y-apple/) The Bible of AI ™ OpenScience • Authors' publicationsFramework based on parameterized images on ResNet to identify intrusions in smartwatches or other related devices 5FITBIT GARMIN In data collecting, Samsung is the only brand which does not compile online information from children under 13 years [16]. However, it does not occur with Apple [17], Fitbit [18] and Garmin [19], that make no distinction between ages. Additionally, all brands chosen for our study, they share information with a third party to analyse metrics and compare results. According to these