Data Logging GCSE ICT
Dec 22, 2015
Data LoggingGCSE ICT
Learning Intentions:•To explore the tern data logging.
•To explore the concept of analogue and digital data and the need for conversion.
Success Criteria:
By the end of the lesson I will be able to:
•Define the term data logging.
•Give two examples of where data logging may take place.
IntroductionThe term 'data logging' refers to collecting or gathering data over a period of time.
How Data is Collected • Sensors are used to take readings or
measurements at regular intervals of their environment. • The sensors could be collecting data on a
wide range of thing such as temperature, humidity, pressure, wind speed, water currents, electrical voltage, pH readings etc. • The sensors may be either analogue or
digital. If they take analogue readings, an Analogue to Digital Converter (ADC) will be needed to convert the signal into digital data which the computer can understand.
• As the sensor takes a reading, the data is sent though a cable or wireless link to the data logger.• The data logger usually stores the data for
a period of time before sending it in a large batch to a computer which will process and analyse it. • A data logger is often a hand-held battery-
operated device which has a large amount of memory.
In a Hospital• When a patient has had a major operation or
is very ill, they may be in the Intensive Care Unit (ICU). • While they are in the ICU, they will be
constantly monitored to make sure that their condition is stable and not deteriorating.• A heart monitor will take readings of their
heart rate and pattern of beats. These readings will be displayed as digital numbers on the monitor itself and they will also be output to a continuous graph so that the doctors can pick up any changes over time.
• Their breathing rate will be monitored and their level of oxygen measured. Alarms will be triggered if their oxygen level goes below a certain amount.• Their temperature will be measured at
regular intervals to monitor whether they have an infection and if so, whether it is responding to treatment.
Water Companies
• Water companies have to constantly monitor the acidity of the water in their reservoirs. They also monitor pollution, chemicals and the number of bacteria in rivers.
In order to do this:•The sensors take measurements of the water.•An ADC converts the analogue signals into digital data.•The data is sent to the data logger where it is stored until called for by the Water Board's computer.•On request, the digital data is transmitted to the Water Board's computer.•Special software (data logging software) takes the data and analyses it.•The results of the analysis are presented as graphs and tables.•The results are printed out.
Racing Cars• Some companies invest millions into
developing state-of-the-art racing cars. • They want to know every aspect of how
their car is performing so that they can ensure the engine is calibrated correctly, the right amount of fuel is being delivered, the best speeds are being achieved (Engine Management System)etc. • Digital electronic dashboards are used
inside the cars. They display data collected by the sensors.
• This data is logged and stored for later analysis by the engineers.• Also, output alarms can be set to alert the driver when certain conditions have been met.•Data can also be scrolled through by the driver pushing a button.
Remote Data Logging• Data often needs to be collected from places
that are nowhere near a nice cosy office. • The data might need to be collected at all
times of the day and night or during weekends when people might be away from work. • Data might also need to be collected from
dangerous places such as volcanoes or from places where it is not practical or safe for a human to be, maybe deep in the ocean, in the upper atmosphere or even on other planets.
• Remote data logging means that the sensors collect data 'out in the field' and pass it to a portable data logger. • The data logger then relays the data either
wirelessly, by fibre-optic cables or possibly even by satellite, back to a computer ready for analysis.
The computer controlling the process
will take readings at regular intervals.
The time interval for data logging is the time
between readings.
If the measured value changes very rapidly then the time interval needs to be rapid as
well, otherwise crucial events will be missed.
The computer will also make a record of when the readings are taken.
The logging period is the total length of time over
which readings are taken..
These are stored in tables. They can be displayed in graphs or passed to an application like a
Spreadsheet.
Logging Intervals and Periods
Data Logging
Sound recording
Heart beat
Oven temperature
Outdoor temperature
Soil dampness
Growth of plants
Destruction of the rain forest
Growth of cities
Global warming
Typical IntervalTypical Interval
Thousandth of a second
Tenths of a second
Minutes
Hours
Days
Weeks
Months
Years
Decades
Advantages of Data Logging• Data Logging can be used in remote or
dangerous situations.• Data logging can be carried out 24
hours a day, 365 days of the year.• Time intervals for collecting data can be
very frequent and regular, for example, hundreds of measurements per second.• Can be set up to start at a time in the
future.• No need to have a person present.• Data logging is often more accurate
because there is no likelihood of human error.
Disadvantages• If the data logging equipment breaks down
or malfunctions, some data could be lost or not recorded• Equipment can be expensive for small
tasks • The equipment will only take readings at
the logging interval which has been set up. If something unexpected happens between recordings, the data will not be collected.
The data logging software will typically store the readings in a table. The data can later be analysed using graph tools.
A graph which could be used in this experiment is a cooling curve graph.
This graph would have time running along the X axis and temperature along the Y axis.
A curve would be drawn to represent the rate in which the water cooled.
Data Logging Graphs
Cooling Curve An example of a graph created
by data logging