Data acquisition in workable forms means digitization of reality. And the conversions of quantitative and qualitative real-time information into numerics. This data is collected in real-time and a dedicated supervisory body is needed for its functions. The acquisition of data requires specialized sensors for every kind of data. For instance, strain is detected with gauges and temperature is sensed by thermal sensors. This real-time collection of real-life data can prove to be a gamechanger for medium to large institutions.
If a proper data acquisition (DAQ) system can be established certain routine and improvised tasks can be automated. For example, if a critically important cold room experiences a rise in its temperature a real-time DAQ system can detect and act upon the inconvenience. This article will discuss the relevance of a DAQ system in an institutional setting and guide the reader about the relevant concepts and components of a DAQ system.
Components of a DAQ system
In a DAQ system armed for recording multiple genres of data, different families of transducers are to be deployed. In-house DAQ is concerned with recording data like temperature, strain, speed, pressure and acceleration etc. these things are monitored by sensors like accelerometers, thermometers and strain gauges.
Sensors are chosen based on various factors related to the setting and environment. Like all other sensors, these sensors also need calibration and repeated reliability tests.
Signal conditioning circuits
The data collected by sensors can not be sent to the analogue to digital converter directly. Some signals might require filtration and conditioning. These signal conditioning systems can be a part of transducers or the ADC. The very role of these systems is to make the collected data error-free, calibrated and worthy of analysis. For instance, a calorimeter might need calibration and auto zero of all noises. A condenser microphone might require circuit noise cancellation. And a strain gauge might need calibration and excitation.
The analogue to the digital conversion system
The sole purpose of this unit is to translate analogue signals into digital visualizable data. The raw data is taken in this unit and converted into readable signals by the processor. The resolution of these ADCS is measured by the number of bits they demonstrate ( 16bit, 18 bit etc). The higher the number, the higher the resolution. Essentially they are measured on a stick with marked ticks. The ticks with centimetres signify lower resolution than that of the ones with ticks in millimetres.
The benefits of a Data Acquisition system
- Improvement of processes and operations are the direct blessing of a DAQ system. The real-time collection of real-life data helps in bringing in the promise of efficiency. It is needless to say with the empowerment of overwhelming amounts of data it is also possible to predict upcoming ordeals and their prevention.
- Data management and storage costs are also reduced by the implementation of a DAQ system. The data collected by such systems are automated and for processing arrangement of data is also automatically performed. Thus human labour in this regard is redundant.
- Data security is also improved due to the elimination of human factors from the equation.
- Quick troubleshooting is also possible if a DAQ is online and functioning as it should. Due to the real-time collection of real-life data, following automated processing, the action time after a prescription is out is significantly low. Thus the problems are resolved at a remarkable pace if a DAQ is working properly. This saves time and helps the different divisions to work properly without unwanted delays.
- Data redundancy can be completely eradicated with the help of a functional DAQ system. The huge amounts of real-life data an institute or organization generates can not be handled by human effort alone. The presence of a parallel automated data analysis and DAQ system reduces the chances of data redundancy, and most of the data is utilized for the benefit of the company.
The DAQ systems are the future in-house monitoring systems that are mostly taken care of by human staff and labourers. That implementation will create human-resource-related problems, especially in a densely populated country like ours. But the implications are lucrative. This implementation of DAQ systems in organizations will mean more profit, as it saves time and reduces the need for human intervention. The future will most likely witness more data-dependent organizations, trying to become more and more efficient by massive utilization of data.