ONTOLOGICAL BASE MODELS MACHINE-TO-MACHINE M2M APPLIED TO THE INTERNET OF THINGS IOT MODELOS BASE ONTOLÓGICOS M2M MÁQUINA A MÁQUINA APLICADOS AL INTERNET DE LAS COSAS IOT

Machine-to-Machine M2M technology being a specific discourse universe of the Internet of Things IoT for the connectivity of intelligent devices, the support of said environment requires a basic conceptual scheme; for which the present article, proposes an evaluation about the different ontological models that consider the M2M and the IoT in simultaneous, recognizing the syntactic and semantic capacity of the interoperability of such devices, from the study of the basic schemes in mention, and identifying its most outstanding properties according to the Quality of Service QoS metric, obtaining the oneM2M ontology as the most appropriate.


INTRODUCTION
Being constantly communicated and informed has become a necessary and peremptory aspect in our current society, a situation that we technology. As a result, conceptual systems with a universe of discourse concerning smart device networks were selected, whose fundamental architecture considers the functional aspects of Quality of Service QoS such as modularity, compatibility with emerging technologies , the hierarchy of components, the formatting of data and the stratification of services, so that said QoS has been proposed as a metric to discuss the various ontologies.
The result was the identification of the functional ontological base model oneM2M as the most appropriate and convenient, since it facilitates the development of syntactic and semantic interoperability of smart appliances (ETSI, 2017), by implementing it as its respective framework.

II. BACKGROUND
The architecture of the Internet of Things IoT facilitates the structuring, interaction and functioning of the components of said network of devices, which is why it is necessary to know the various ways in which entities that can be formally organized can be organized. they configure the IoT (Vermesan, 2013), as their characteristics and their possible relationships with each other within a specific domain. The latter is what is known as "ontology" (Grønbaek, 2008  locations, etc., that are intended to be included in other ontologies through OWL imports (Compton, et al., 2012) are not described (W3C, 2011).  The ontology can be used to focus on any one (or a combination) of a series of perspectives (ibid.): • A sensor perspective focused on what, how and when it perceives.
• A data or observation perspective, with a focus on related observations and metadata.
• A system perspective, with a focus on sensor systems.
• A property and property perspective, with a focus on what can be detected from them.
The modules, as described here, allow these views to be further refined or grouped into

M3 ontology
The framework Machine-to-Machine Measurement M3 helps developers semantically annotate M2M data and build new applications by reasoning in M2M data from heterogeneous IoT domains. The M3 frame is shown in Figure 3 and consists of several layers as follows (Gyrard, et. Al., 2014): • The perception layer is composed of physical devices such as sensors, actuators and RFID tags (ibid.).
• The data acquisition layer retrieves the data from the sensors (SenML)

Common Services Layer
Network Services Layer    IOT Lite is an ontology that is created to be used with a common taxonomy that makes it easy to describe the units and number of classes that devices in the IoT can measure. This hierarchy represents individuals in ontology and is based on well-known taxonomies such as qu and qudt (ibid.).
As an example of a sensor device, the SmartCSR IoT Node is taken. Figure 9 shows a conceptual scheme of the sensor device mentioned (ib.). and particular, such as layered organization , the structure by modules, the formatting of the data, the ontological pattern, the query of graphs, the syntactic and inference rules.
In  in which the service layer (equivalent to the business layer) and managing the mentioned above ontology, allows to integrate the various devices for its management as follows: • Subscription and notification devices through MQTT.
• Devices restricted by CoAP • Autonomous devices through REST In this way, any device or machine is able to connect permanently to the Internet either directly (GSM) or indirectly (Gateway) and send requests and receive responses at the appropriate time (subscribe-publish), which facilitates its implementation in a lot of contexts.