We develop Dashboards for the diagnosis and prevention of Home Automation and IoT Systems.

Through Big Data architectures, we incorporate into the Inmotics and Home Automation solutions the obtaining and storage of a large volume of unstructured data from the different IoT devices, as well as the generation of analysis reports and monitoring of the different systems that coexist.

With all this, we obtain the necessary diagnosis, control and agile location of incidents and anomalies in any of the systems or facilities.

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Our KALENA solution allows you to manage your workspaces at any time, from anywhere.

KALENA is a software platform to manage the reservation of spaces and corporate resources of the company, such as meeting rooms, workstations and parking spaces.

In a centralized way and from a single interface, KALENA integrates a multitude of calendars, dynamic maps of the occupation of spaces, and home automation devices and IoT sensors: devices for detecting presence, counting people and capacity, devices for automatic opening of barriers, control of audiovisual elements, lighting, signage displays, touch screens, etc.

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Monitoring and preventive analysis of assets in motion.

Usually assets “in motion”, such as a fleet of vehicles, are not integrated and are only cataloged with the initial starting situation.

With our solutions for Asset Management, we were able to capture the heartbeat of said moving assets to monitor in real time, which allows preventive analysis of blocking incidents in the operation.

We integrate heterogeneous sources of "beats" for more accurate diagnostics and predictive analysis of routine learning.

In the management of home automation systems, there are usually blocking incidents in the operation of unknown origin a priori, which are escalated to the integrator closest to the user interface. The reality we are faced with is that there is no data persistence, there is no possibility of collecting all data sources, there is no correct diagnosis or an adequate RCA analysis is not carried out, and therefore there are losses of time and inefficiencies in resolution.

Our solution integrates by “superposition” heterogeneous sources of beats, of a different nature. The data is stored and persists, which allows a precise diagnosis of the situation, a predictive analysis for a learning routine, and the correct resolution of the incident.

Intelligent monitoring of resources consumption, analyzing behavior patterns.

Thanks to the integration of heterogeneous sources, we can also intelligently control and monitor resources consumption, analyzing user consumption patterns and / or specific areas, detect faults in real time, identify consumption saving measures, and establish correlations and key performance indicators for each resource.