Environmental and Pollution Sensing
Literally an explosion is occurring in the context of IoT. The consequence is natural that more and better sensors for the wide range of different phenomena arise every day. In particular, those related to the control of our environment, has had special emphasis.
Aware of this new reality, TLM has been concerned with extending its connection and interaction to this new world of possibility by adding its knowledge in the treatment of these signals and its communication with the different control systems, provided by TLM as well other legacy applications of its clients.
The main areas of action can be exemplified as follows:
- Air and sound pollution
- Pollution of natural water (rivers, lakes and sea) and control
- Swimming pools (water parks)
- Presence of different types of elements, such as aluminum, iron, magnesium, etc.
The TLM has special expertise in receiving this data and transmit it to the control systems, triggering the messaging and other activities of reaction predicted, in other words, Sensing is more than just having sensors. There is sometimes a temptation to reduce environmental sensing to the use of a set of sensors, capable of detecting specific substances or factors. However, choosing a sensor is only a small part of the challenge. Fundamentally, sensors allow us to "see" things that otherwise would not be possible, such as temperature, humidity, carbon dioxide (CO2), and volatile organic compounds. This condition is represented by electrical signals, which must be conveniently translated and treated. The central question is how these signals should be handled through the chain of communication and analytical tools that ensure data quality and provide timely and relevant insights. For TLM, this integrated system is the platform of Environmental Intelligence - a combination of sensors, communications, cloud computing, artificial intelligence, interfaces, systems, training and technical support, and operating in a coordinated and productive way, generating benefits.