1.2.2.6: Input Devices

Input devices

Data may enter an information system in a variety of different ways, and the input device that is most appropriate will usually depend on the type of data being entered into the system, how frequently this is done, and who is responsible for the activity. For example, it would be more efficient to scan a page of typed text into an information system rather than retyping it, but if this happens very seldom, and if typing staff are readily available, then the cost of the scanner might not be justified. However, all of the input devices described in this chapter have at least one thing in common: the ability to translate non-digital data types such as text, sound or graphics into digital (i.e. binary) format for processing by a computer.

Let’s apply an agricultural perspective to the idea of data input devices in an information system:

 

1. Scanning vs. Typing:

In agriculture, different methods are used to collect and record data about crops, livestock, and farm operations. For instance, if you need to record detailed field observations, you might use a drone to capture aerial images instead of manually writing notes. Similarly, using a digital scanner to input typed text into a system can be likened to using a modern sensor to gather soil moisture data rather than relying solely on manual measurement.

 

2. Choosing the Right Tool:

Just as different farming tasks require specific tools—such as using a combine harvester for large-scale grain harvesting versus a hand trowel for planting small quantities of seedlings—the choice of data input device depends on the nature of the data and its frequency of use. For instance:

• Frequent Data Collection: If you frequently measure soil pH levels across multiple fields, you might use a portable digital pH meter to streamline the process, similar to how a regular input device like a keyboard or scanner is used frequently for data entry.
• Infrequent Data Collection: For less frequent tasks, such as taking periodic crop yield assessments, a more specialized device might be used, just as a high-end scanner might be justified for occasional but detailed document digitization.

 

3. Cost vs. Efficiency:

Just as investing in high-end agricultural equipment (like a GPS-guided tractor) makes sense for large-scale operations where efficiency gains justify the cost, the decision to invest in sophisticated data input devices (like high-speed scanners or voice recognition systems) depends on whether the efficiency improvements outweigh the costs. For smaller operations or infrequent tasks, simpler, more cost-effective solutions (like manual data entry or basic measuring tools) might be sufficient.

 

4. Translating Data into a Usable Format:

In agriculture, translating physical observations into useful data might involve converting visual observations of crop health into digital records, much like how input devices translate non-digital data (text, sound, graphics) into a digital format. For example:

• Visual Data: Just as drones or cameras capture visual information of crops, input devices like scanners convert physical documents into digital formats.
• Sound Data: Microphones recording animal sounds or machinery noise can be translated into data for analysis, analogous to how voice input devices capture and convert spoken information into text.

 

5. Role of Each Device:

Each agricultural tool or device serves a specific purpose, enhancing productivity and precision in its area of use. Similarly, each data input device—whether it's a keyboard, scanner, or microphone—has a role in translating different types of data into a digital format for processing. Just as farmers select tools based on their specific needs, choosing the right input device depends on the type and frequency of data collection, as well as the efficiency and cost considerations.

In summary, much like selecting the appropriate agricultural equipment based on the task at hand, choosing the right data input device involves evaluating the nature of the data, how often it needs to be collected, and the overall cost-effectiveness. Each device plays a role in converting real-world data into a digital format, just as different tools help in converting physical farm activities into productive outcomes.