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Data collection methods

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Introduction

The process of data collection is an essential part of our daily routine activities. The data

collection process can be identified as the guidance engine, which usually drives us to a quality

improvement in areas one is investigating. For instance, Capri's (2015) reading on the manual

data collection has mainly assisted many individuals in understanding how data is collected. This

has primarily made a promising discovery of how things are mainly operating as one mostly

becomes more interested in the data collection process. Through the data collection, we can

investigate wide occurrences of the research questions.

What were the traditional methods of data collection in the transit system?

Several methods of data collection were traditionally used in the transit system. The

traditional methods which were mainly used included invasive techniques. This method was used

primarily to use a piezo- sensor or a magnet as a local data collection method. There was the use

of a human surveyor in the terrain or from a video in collecting data (Lai, et al., 2020). This was

mainly done through both direct and indirect personal interviews. The human surveyor mostly

involved the idea of questionnaire use. Radars and other simple techniques or a form of image

analysis were mainly used through a machine vision. The traditional methods were primarily

used as they offered a good platform for collecting data effectively.

Why are the traditional methods insufficient in satisfying the requirement of data

collection?

The traditional methods of data collection were not more effective as they had some

limitations. The data collected was not to the standards as there were not many considerations

with the required standards. This had an impact on the comparability of the data collection. The

context of data collection was not much considered. For instance, those who were collecting the

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data were not much valued. There was a complexity as there were many risks and dangers in the

data collection process (Baumfeld Andre, et al., 2020). The barriers made it difficult to attain the

quality requirements of the data. Finally, the data collected through the traditional methods were

not to the standards as there was a lack of training in collecting data. These challenges made it

difficult for the conventional approaches to be more satisfying in data collection.

Give a synopsis of the Capri (2015) case study and your thoughts regarding the

requirements of the optimization and performance measurement requirements and the

impact to expensive and labor-intensive nature

After reading the chapter by Capri (2015) on manual data collection, I realized an

apparent breakdown. This chapter is mainly regarding equipping the researchers with the best

techniques to apply in the data collection process. This chapter has helped chiefly the

engineering sector be more conversant with data collection methods. According to my thoughts, I

would mainly have to appreciate all those individuals who would take time and read this chapter;

they will be more equipped with the best data collection methods. Through this idea, all the

requirements and best measurements will be emphasized; hence the impacts to the expensive and

labor-intensive nature will be utilized effectively.

The Capri (2015) chapter reading has mainly helped several individuals minimize the

expense they would experience in data collecting processes.

This chapter has taught us how we can work in the data collection process without

experiencing many challenges. There is also an improvement as a whole as the issue of labor-

intensive is well outlined in nature. The techniques and alternatives offered are mainly likely to

impact the engineering sector as a whole. This is evidenced as there is a good optimization and

an improvement in the performance requirements.

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In conclusion, the engineering department has been identified to improve in general as

there are guidelines and processes pertaining there data collection methods. As we are today, we

cannot compare this as it was before. There were several challenges which impacted the data

collection process. In the current situation, we are happy as there is a clear light of where we will

be in the future.

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References

Baumfeld Andre, E., Reynolds, R., Caubel, P., Azoulay, L., & Dreyer, N. A. (2020). Trial designs

using real‐world data: The changing landscape of the regulatory approval

process. Pharmacoepidemiology and drug safety, 29(10), 1201-1212.

Lai, X., Teng, J., & Ling, L. (2020, September). Evaluating Public Transportation Service in a

Transit Hub based on Passengers Energy Cost. In 2020 IEEE 23rd International

Conference on Intelligent Transportation Systems (ITSC) (pp. 1-7). IEEE.

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