What is machine learning? Sure, many of you have heard or read this term but you still have doubts. The current technological landscape places innovation as a strategic center in companies. The emergence of new technologies such as machine learning has driven a change in the way things are done: the adoption of data analysis in companies is in full expansion and is presented as an asset of great value for your business projection.
What is machine learning: definition
Machine learning is a discipline within the field of artificial intelligence that automates the construction of analytical models. It is a method of data analysis that identifies complex patterns and can predict behaviors.
Machine learning has developed techniques with computing as a basis that allow systems to “learn”, that is, identify millions of patterns from the data obtained to incorporate new knowledge that makes them react in different future situations. The expert system, at the same time, that it feeds on new data, perfects its behavior autonomously, thus achieving an optimum level of efficiency.
Nowadays both SMEs and large companies generate huge volumes of data, so the challenge that lies ahead is how these can be analyzed to generate information that contributes to efficiency and cost optimization.
Main applications of machine learning in IoT
Machine learning is integrated into advanced IoT platforms to predict patterns from the analysis of data obtained from sensors that measure a large number of variables for tasks such as:
- The monitoring of air quality in different environments (smart cities, farms, the environmental industry, etc.).
- The monitoring of meteorological variables in precision agriculture (smart agro).
- The monitoring of structural health in infrastructures (buildings, bridges, industrial plants, etc.).
- Industrial monitoring in factories (industry 4.0).
For the operation of an expert system, it is important to have a secure server that guarantees the connection and transport of large volumes of data with high speed and low latency to ensure assistance in case of failures.
Advantages of machine learning in IoT applications
- It is a tool that guarantees organizations the quality and integrity of the stored data.
- Predicts trends and needs based on the interpretation of huge volumes of data. For organizations, it translates into better decision-making, in which human resources, material resources and a large amount of time were used up to now.
- Applied to industrial processes, predictions are generated that can help maintenance managers to make decisions such as the optimization of machinery stops, in order to lengthen their useful life, increase efficiency and improve productivity.
- In air quality monitoring applications, the prediction through machine learning allows extending the life of the sensors and analyzers.
ENVIRA is specialized in the development of integral IoT solutions for the monitoring of situations in which environmental value is significant. This company has developed an artificial intelligence tool based on machine learning for the early detection of anomalies in the operation of monitoring instruments of various variables. The system is formed by a combination of expert system and machine learning that analyzes the input data and notifies those responsible for possible anomalies to avoid improper use of them in case of suspicion of being incorrect.