=Paper=
{{Paper
|id=Vol-2030/HAICTA_2017_paper45
|storemode=property
|title=User-Technological Index of Precision Agriculture: Methods of Collecting data
|pdfUrl=https://ceur-ws.org/Vol-2030/HAICTA_2017_paper45.pdf
|volume=Vol-2030
|authors=Jan Jarolímek,Jiri Vanek,Jan Masner,Pavel Simek,Edita Silerova
|dblpUrl=https://dblp.org/rec/conf/haicta/JarolimekVMSS17
}}
==User-Technological Index of Precision Agriculture: Methods of Collecting data==
https://ceur-ws.org/Vol-2030/HAICTA_2017_paper45.pdf
User-Technological Index of Precision Agriculture:
Methods of Collecting data
Jan Masner1, Jan Jarolímek1, Jiří Vaněk1, Pavel Šimek1, Edita Šilerová1,
1
Department of Information Technologies, Czech University of Life Sciences Prague, Czech
Republic, e-mail: masner@pef.czu.cz
Abstract. User-Technological Index of Precision Agriculture (UTIPA) is a
comprehensive system based on mutual sharing of opinions and experience
within community of people related to precision agriculture - farmers,
technology suppliers and researchers. The main goal of UTIPA is to present
the calculated index level for particular technology (method) for precision
agriculture and compare it to other technology. The index is based on
evaluation of technological advancement and usefulness for agricultural
practice. The paper discusses methods for collecting data for questionnaire in
general. It elaborates on the technical solution developed for data collection for
UTIPA. The system allows data collection as well as visualizations available to
all participants.
Keywords: precision agriculture, survey, questionnaire, farmers, web,
visualization
1 Introduction
The concept of precision agriculture is in the interest of the professional public since
the 1990s. It generalizes the effort to identify solutions, tools and processes that can
improve productivity and profitability while protecting the environment (Cambouris
et al. 2014). Precision agriculture plays a vital role in increasing production and is
seen as part of the agricultural process efficiency and environment-friendliness. In
summary, the concept of precision agriculture is based on observations and
measurements followed by the appropriate responses - for example through the
introduction of new technology or by changing manufacturing processes. Precision
agriculture technologies allow farmers to identify problems and opportunities and
apply solutions with far greater accuracy (Lindblom et al. 2016).
A key factor in deciding whether a particular technology should be incorporated to
practice is the understanding of agricultural production processes as well as the
technology itself. Workers in agriculture management must choose among various
options for applied research and technology and in this decision-making process
there is a necessity to merge previous experience of the staff and the introduction of
new technologies and procedures (Kumhala, F; Kroulik, M; Masek, J; Prosek 2003).
It is vital to establish effective decision models and support resources for that
particular phase of the production process.
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The data for evaluation is collected from farmers, technology suppliers,
researchers and general public. The optimal way to get the data is to run a survey.
Therefore, there is a need to spread questionnaires and get them back. Questionnaires
can be disseminated in two major forms - printed on paper or electronically via
Internet. As (Gordon & McNew 2008) suggests, it is important to make informed
decisions as to the right technology which to implement. Besides, many authors and
studies suggest the internet as the best carrying medium (Lumsden 2005; Van Selm
& Jankowski 2006; Andrews et al. 2003). On the other side, web based surveys
generally exhibit a lower response rate (Fan & Yan 2010; Hamilton 2009).
2 Materials and Methods
The purpose of the User-Technological Index of Precision Agriculture (UTIPA) is to
propagate the knowledge of users, suppliers and researchers in the use of modern
technology in agriculture. It is primarily based on a five-point evaluation of selected
technologies (methods) of precision agriculture in terms of technological
advancement and applicability in agricultural practice. It evaluates technologies in
principle and does not reflect specific products, brands or manufacturers (Jarolímek
et al. 2017).
The questionnaire for UTIPA is compiled from several general questions (email,
country, background) and rating for each technology (1 – 5 for both evaluation
criteria). Rating is based on individual knowledge and experience of the respondents.
An important characteristic of the evaluated technology is also its unfamiliarity
among the respondents. The web based version of the rating is shown in Figure 1.
Many surveys usually only spread a questionnaire and collect data. Results are
delivered to the participants only occasionally. On the contrary, UTIPA works on the
principle of "what data I provide is the type of data I gain access to". Therefore, each
participant who filled the questionnaire has access to the results and can benefit from
them.
Fig. 1. The online form of questionnaire. Rating for technologies.
The system of data collection for UTIPA works on a simple principle. Each
participant fills email address, basic information and the ratings for selected
technologies (approximately around 10, based on the questionnaire and the
occasion). To validate the contribution a confirmation email is sent to the given
address. Once the provided link is clicked, the data are verified and the participant
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can create a password. The user is automatically signed in and can immediately
access all the collected data. The whole process is shown in Figure 2.
Department of Information Technologies runs a survey among Czech farmers
about their ICT equipment every two years since 2010. Questionnaires are primarily
spread over the Internet via emails. Aside from that, some of questionnaires are sent
in paper form via classic post. The return rate of the printed questionnaires is still on
a significantly higher level. In addition, the level of ICT equipment among Czech
farmers is lower than a national average. The level of a knowledge is significantly
low in long-term as well (Šimek et al. 2014). As mentioned above, the return rate of
the printed form of questionnaire is higher than the electronic form. Therefore, the
questionnaire for UTIPA is spread in printed form besides the electronic as well. The
data gathered this way is inserted into the system manually later.
Fig. 2. The process of filling questionnaire and access to the data.
3 Results
User-technological Index of Precision Agriculture is a complex system that
includes a methodology for collection, processing and presentation of data and
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software, which is available via a web interface. The software is optimized for
mobile devices. It will be also possible to use native applications for iOS and
Android operating systems (currently under development).
The data collection system for the questionnaire was maximally simplified. While
user is filling the form all data are continuously saved via AJAX. This approach
allows having the data even when some participants do not finish the questionnaire
for whatever reason. The user can even continue filling it in later.
After successful email confirmation all participants have access to the collected
data. There are currently two main views. Each view then can visualize the data in a
different way.
3.1 General results
This view contains three visualizations. The main one shows the results for each
technology in a chart as shown in Figure 3. The X-axis indicates applicability in
agricultural practice and the Y-axis indicates technological advancement. Each point
in the chart represents certain technology. When the number is hovered over,
additional information is displayed. It contains name of the technology, exact values
for both evaluation criteria, and the computed UTIPA index. The index consists of
two parts, the numeric value and an additional character. The numeric part of the
index has values between 0 and 1 and reflects the degree of usefulness and
sophistication of the technology. The numeric value can be supplemented with the
character, which can be either “u” or “t” and expresses better ranking in favor of
applicability in practice or technological advancement - the location in the chart in
Figure 3. The methodology for calculation of the index was published by (Jarolímek
et al. 2017). In addition, users can compare own evaluation with the calculated
values. The visualization is shown in Figure 3.
Fig. 3. Visualization of the General results with comparison of own evaluation.
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Participants of the survey have also an option to indicate the unfamiliarity with
certain technology. It is an important characteristic for the results. The output is then
a comparison of unfamiliarity of technologies.
3.2 List of technologies
Another view lists all the technologies with the calculated values for each
technology. It shows the UTIPA index, both criteria value and technology
annotation. If the user has not rated the technology, the rating option is shown. In the
detail page of each technology, there is a heat map chart showing graphical
presentation of scatter of all the ratings (Figure 4). Users have also the possibility to
change their ratings when the technology evolves, opinion changes or their
knowledge raises.
Fig. 4. Heat map visualization of the scatter of ratings by individual respondents.
4 Conclusion
User-Technological Index of Precision Agriculture is a complex system for the
international community of people related to precision agriculture, it is accessible to
anyone who respects the rules of use. It works on the principle of "what data I
provide is the type of data I gain access to".
The proposed system for collecting questionnaire data was designed primarily as a
web application gathering data online. It is also simultaneously spread in a printed
form. The data is continuously saved during the filling of the online form. In
addition, the system provides access to the visualizations of collected data for all
participants. Moreover, as the number of technologies increases it will be possible to
rate them individually.
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The UTIPA index benefits all the stakeholders. Farmers can find out whether a
given technology is useful and has real importance. Suppliers need to know what
their customers (farmers) want or expect, but also how they perceive their products.
For academia it can be a source of data for science and research. The importance and
significance of the index grows with the number of respondents.
Future research will focus on two main areas. Firstly, there will be analyzed the
data from collecting surveys. The question is to determine the optimal way of
spreading surveys of this type, where and why people stopped filling the form etc.
Secondly, the visualization of the gained data will be enhanced. New types of
displays and comparisons will be introduced.
UTIPA system is freely available as a web application at https://www.utipa.info/.
Acknowledgments. The results and knowledge included herein have been obtained
owing to support from the following institutional grants. Internal grant agency of the
Faculty of Economics and Management, Czech University of Life Sciences in
Prague, grant no. 20171023, „User-Technological Index of Precision Agriculture “.
References
1. Andrews, D., Nonnecke, B. & Preece, J. (2003) Conducting Research on the
Internet : Online Survey Design , Development and Implementation
Guidelines. International Journal of Human-Computer Interaction, 16(2),
pp.185–210.
2. Cambouris, A.N. et al. (2014) Precision Agriculture in Potato Production.
Potato Research, 57(3–4), pp.249–262.
3. Fan, W. & Yan, Z. (2010) Factors affecting response rates of the web
survey: A systematic review. Computers in Human Behavior, 26(2),
pp.132–139.
4. Gordon, J.S. & McNew, R. (2008) Developing the online survey. The
Nursing clinics of North America, 43(4), pp.605–19
5. Hamilton, M.B. (2009) Online Survey Response Rates and Times. Ipathia,
Inc., N/A(White Paper), pp.1–5.
6. Jarolímek, J. et al. (2017). User-Technological Index of Precision
Agriculture. Agris on-line Papers in Economics and Informatics, 9(1),
pp.69–75. Available at: http://online.agris.cz/archive/2017/01/06/.
7. Kumhala, F; Kroulik, M; Masek, J; Prosek, V. (2003) Development and
testing of two methods for the measurement of the mowing machine feed
rate. Plant Soil and Environment, 49(11), pp.519–524.
8. Lindblom, J. et al. (2016) Promoting sustainable intensification in precision
agriculture: review of decision support systems development and strategies.
Precision Agriculture. Available at:
http://link.springer.com/10.1007/s11119-016-9491-4.
9. Lumsden, J. (2005) Guidelines for the Design of Online-Questionnaire.
National Research Council Canada, NRC/ERB 11(June), pp.44–64.
388
10. Van Selm, M. & Jankowski, N.W. (2006) Conducting online surveys.
Quality and Quantity, 40(3), pp.435–456.
11. Šimek, P., Stočes, M. & Vaněk, J., 2014. Mobile access to information in
the agrarian sector. Agris On-line Papers in Economics and Informatics,
6(2).
389