The collaboration between Blautic and Grupo Chillida represents much more than a business agreement: it is a technological alliance that combines more than a century of industrial experience with the most advanced capabilities in digitalization, data analytics, and machine learning.
This synergy has made it possible to evolve traditional technical alarm systems into intelligent, connected, and predictive solutions, especially designed for critical environments where safety, operational continuity, and energy efficiency are top priorities.
The key data behind our technological alliance
Grupo Chillida, a century-old company and a benchmark in its sector, has historically stood out for delivering services under the highest standards of quality and reliability. Meanwhile, Blautic contributes its expertise in hardware design, advanced software development, and data analytics applied to security systems.
As a result of this technological alliance, both companies have developed solutions that integrate multiple sensing technologies to capture key information in industrial and commercial facilities. A prominent example is the Alert-Cool system, a platform designed to monitor critical variables such as:
- Temperature
- Humidity
- Presence of refrigerant gases
- Sensitive environmental parameters
Currently, Chillida’s databases manage more than 50 million data points annually generated by these systems. This volume of information not only demonstrates the scale of the project, but also highlights the strategic importance of intelligent data processing.
The combination of industrial expertise and advanced digitalization has made it possible to transform raw data into actionable insights, optimizing processes and improving real-time decision-making.
How We Apply Security and Technical Alarm Systems in Critical Environments
Security and technical alarm systems play a fundamental role in environments where an incident can result in financial losses, health risks, or serious operational disruptions.
In facilities such as cold storage rooms, logistics centers, hospitals, or industrial spaces, constant monitoring is essential. Through strategically distributed sensors, the systems developed by Blautic and Grupo Chillida make it possible to:
- Detect thermal deviations.
- Identify gas leaks.
- Monitor critical environmental conditions.
- Activate immediate response protocols.
All the information collected is centralized in Chillida’s cloud, where it is managed by a 24/7 Control Center. This model ensures continuous monitoring and the ability to respond immediately to any alert.
In addition, the development of mobile applications has represented a significant leap in daily operations. Technicians can access the real-time status of facilities, receive instant notifications, and review historical data from any location. This optimizes installation, monitoring, and maintenance processes, reducing response times and increasing efficiency.
In short, technical alarm systems have evolved from a reactive model—based solely on triggering alarms in response to evident failures—toward a proactive and connected model.o.
Machine Learning Applied to Technical Alarm Management
One of the most significant advancements within this technological alliance has been the incorporation of machine learning algorithms into the management of technical alarms.
Traditionally, systems were configured using fixed thresholds defined by technical expertise. If a parameter exceeded a certain value, an alarm was triggered. Although effective, this approach had limitations: it did not always account for complex patterns or subtle anomalous behaviors.
With the integration of machine learning, systems can now:
- Analyze large volumes of historical data.
- Identify normal behavioral patterns in each facility.
- Detect anomalies before they become critical incidents.
- Customize alerts according to the operational context.
This approach makes it possible to evolve from static alarms to intelligent and adaptive alarms. Each facility has its own behavioral “digital footprint,” and predictive models continuously learn to refine detection.
The result is a significant reduction in false alarms and an improvement in alert accuracy, which translates into greater operational reliability and optimized use of technical resources.
Real-Time Monitoring and Predictive Event Detection
Real-time monitoring is one of the fundamental pillars of today’s systems. However, the true differentiating value lies in the ability to anticipate issues.
Thanks to continuous data processing and the use of intelligent algorithms, it is possible to identify early signals that indicate a potential future failure. For example:
- Progressive upward temperature trends.
- Repeated micro-variations in gas pressure.
- Changes in energy consumption patterns.
When analyzed together, these indicators make it possible to trigger predictive alerts before a failure occurs.
This approach not only enhances safety, but also has a direct impact on profitability. Early detection reduces repair costs, minimizes downtime, and prevents product losses in critical facilities.
Additionally, the automatic generation of reports and dashboards provides a strategic overview for technical managers and executives, supporting data-driven decisions based on real-time, up-to-date information.