4.4 Awareness towards Drone Technology
4.4.3 Awareness towards the Benefits of Drone Technology
are also three respondents in this age group who have never heard about drone technology before. Whereas, among the respondents aged “35 to 44 years old”, it is reported that nine of the respondents have often and always heard about drone technology. The frequency of hearing of drone technology is reported the highest in respondents aged “25 to 34 years old” where 24 respondents have often and always heard about drone technology.
Since most of the respondents aged “below 25 years old” have rarely heard about drone technology as compared to the other age groups, the respondent’s awareness towards the application of drone technology is, therefore, the lowest among the three tested age groups. Moreover, since the respondents aged “25 to 34 years old” have more often heard about drones than the respondents aged “35 to 44 years old”, it therefore perceived a higher awareness towards the applications of drone technology.
Table 4.8: Mean of the Agreements on the Benefits of Drone Technology in the Construction Industry.
Benefits of Drone Technology Rank Mean Average
Mean Improved jobsite communication - real-time
jobsite monitoring and site inspection
1 4.15 3.87
Better jobsite photo documentation - consistent jobsite progress photo capture
1 4.15 Worker safety - reduction of inspection risk on
hard-to-reach area
3 4.13 Improved stakeholder communication - on-
demand visual imagery through cloud-based platform
4 4.07
Site security - regular drone security patrol over the site
5 4.05 Time saving - efficient data collection and
reporting
6 3.95
Time saving - reduce field time 7 3.94
Dispute reconciliation - drone data and imagery provide clear evidence against the mistake
7 3.94 Cost saving - prevent costly misaligned
construction
9 3.86 Worker safety - early safety hazard
identification
10 3.80 Better post-project documentation - assessment
on the documented changes and visual imagery captured by drone for future construction quality improvement benchmarking
10 3.80
Site security - early fire hazard identification through thermal camera mounted drone
12 3.79 Cost saving - early construction deviation
detection
13 3.77
Table 4.8 (Continued)
Benefits of Drone Technology Rank Mean Average
Mean Cost saving - reduction of surveying expenses 14 3.76
Time saving - enable faster decision making 15 3.75 High accuracy - reduce the need for re-work and
re-measurement
16 3.73 Dispute avoidance - early information
discrepancy detection through pre-construction topographic survey
16 3.73
Business competitiveness - enable better workflow management
18 3.71 Business competitiveness - enable contractor to
make ambitious bids
19 3.63 High accuracy - reduction of human error in data
collection
20 3.61
Kruskal-Wallis test was conducted to examine if there is a statistically significant difference in the awareness towards the benefits of drone technology in the construction industry between the three age groups “below 25 years old”, “25 to 34 years old”, and “35 to 44 years old”. The null hypotheses generated for the Kruskal-Wallis test are:
(i) Null Hypothesis (H0): There is no difference between age groups in the awareness towards the benefits of drone technology in the construction industry.
(ii) Alternative Hypothesis (H1): There is a difference between age groups in the awareness towards the benefits of drone technology in the construction industry.
The alpha value adopted is 0.05 with two degrees of freedom. The null hypothesis is rejected when an asymptotic significance value less than or equal to 0.05 is obtained. It indicated a statistically significant difference in the result.
The outcome of the Kruskal-Wallis test on the awareness towards benefits of drone technology across the age groups is summarised in Table 4.9.
Table 4.9: Kruskal-Wallis Test on the Awareness towards Benefits of Drone Technology.
No Benefits
Below 25 years old (n = 34)
25 - 34 years old (n = 51)
35 - 44 years old
(n = 30) Asymp.
Sig.
Mean
Rank Rank Mean
Rank Rank Mean
Rank Rank
1 Cost saving - prevent costly misaligned construction 46.56 18 65.71 8 57.87 4 0.021*
2 Cost saving - reduction of surveying expenses 51.84 9 63.34 18 55.90 9 0.224
3 Cost saving - early construction deviation detection 43.93 20 66.65 3 59.25 1 0.004*
4 Time saving - reduce field time 50.10 13 65.37 12 54.42 10 0.063
5 Time saving - efficient data collection and reporting 51.29 10 64.80 15 54.03 11 0.099
6 Time saving - enable faster decision making 53.18 6 67.51 2 47.30 20 0.010*
7 Worker safety - reduction of inspection risk on hard-to- reach area
52.44 8 64.21 16 53.75 12 0.131
8 Worker safety - early safety hazard identification 47.49 16 65.38 11 57.37 6 0.027*
Note: * indicates the mean rank difference is significant at 0.05 significance level.
Table 4.9 (Continued)
No Benefits
Below 25 years old (n = 34)
25 - 34 years old (n = 51)
35 - 44 years old
(n = 30) Asymp.
Sig.
Mean
Rank Rank Mean
Rank Rank Mean
Rank Rank
9 Site security - regular drone security patrol over the site 45.71 19 66.59 4 57.33 7 0.007*
10 Site security - early fire hazard identification through thermal camera mounted drone
51.15 11 65.86 7 52.40 13 0.049*
11 High accuracy - reduction of human error in data collection
49.94 14 68.25 1 51.97 14 0.007*
12 High accuracy - reduce the need for re-work and re- measurement
55.65 3 65.43 10 48.03 18 0.048*
13 Improved stakeholder communication - on-demand visual imagery through cloud-based platform
51.07 12 62.56 9 58.10 3 0.248
14 Improved jobsite communication - real-time jobsite monitoring and site inspection
56.22 1 63.33 19 50.95 15 0.177
Note: * indicates the mean rank difference is significant at 0.05 significance level.
Table 4.9 (Continued)
No Benefits
Below 25 years old (n = 34)
25 – 34 years old (n = 51)
35 – 44 years old
(n = 30) Asymp.
Sig.
Mean
Rank Rank Mean
Rank Rank Mean
Rank Rank
15 Better jobsite photo documentation – consistent jobsite progress photo capture
55.84 2 63.64 17 50.87 16 0.157
16 Better post-project documentation – assessment on the documented changes and visual imagery captured by drone for future construction quality improvement benchmarking
47.19 17 64.96 14 58.43 2 0.038*
17 Dispute avoidance – early information discrepancy detection through pre-construction topographic survey
53.72 5 66.17 6 48.97 17 0.031*
18 Dispute reconciliation – drone data and imagery provide clear evidence against the mistake
53.09 7 62.32 20 56.22 8 0.350
19 Business competitiveness – enable contractor to make ambitious bids
54.31 4 66.40 5 47.90 19 0.026*
Note: * indicates the mean rank difference is significant at 0.05 significance level.
Table 4.9 (Continued)
No Benefits
Below 25 years old (n = 34)
25 - 34 years old (n = 51)
35 - 44 years old
(n = 30) Asymp.
Sig.
Mean
Rank Rank Mean
Rank Rank Mean
Rank Rank
20 Business competitiveness - enable better workflow management
47.66 15 65.05 13 57.73 5 0.036*
Average Mean Rank 50.92 - 65.18 - 53.94 - -
Note: * indicates the mean rank difference is significant at 0.05 significance level.
The results showed that there is a statistically significant difference in the awareness across the age groups towards the benefits of drone technology, except for the benefits of drone technology in:
(i) Cost saving - reduction of surveying expense (Asymp. Sig. = 0.224).
(ii) Time saving - reduce field time (Asymp. Sig. = 0.063).
(iii) Time saving - efficient data collection and reporting (Asymp.
Sig. = 0.099).
(iv) Worker safety - reduction of inspection risk on hard-to-reach area (Asymp. Sig. = 0.131).
(v) Improved stakeholder communication - on-demand visual imagery through cloud-based platform (Asymp. Sig. = 0.248).
(vi) Improved jobsite communication - real-time jobsite monitoring and site inspection (Asymp. Sig. = 0.177).
(vii) Better jobsite photo documentation - consistent jobsite progress photo capture (Asymp. Sig. = 0.157).
(viii) Dispute reconciliation - drone data and imagery provide clear evidence against the mistake (Asymp. Sig. = 0.350).
The null hypothesis of these eight statements of benefits is failed to reject as the asymptotic significance value is more than the alpha value of 0.05, thus there is no sufficient strong evidence to reject the null hypothesis and to conclude that the awareness across the age groups towards the eight statements of benefits of drone technology is different. However, the null hypothesis for the remaining 12 statements pertaining to the benefits of drone technology is rejected as the asymptotic significance value obtained is lesser than 0.05.
There is no significant difference in the awareness across the age groups towards the eight benefits of drone technology because the respondents perceived about the same agreement towards the eight benefits of drone technology. This may because they have heard or get to know that the eight benefits have been reap by the drone adopters in the construction industry.
Therefore, they are more aware of the benefits. Moreover, it can be deduced that the respondents are holding similar expectations to reap the eight benefits
when they adopt drone technology. The discussions on the respective eight benefits of drone technology can be referred at subchapter 2.9.
The outcome of the Kruskal-Wallis test also revealed that the respondents aged “25 to 34 years old” perceived the highest awareness towards the benefits of drone technology (average mean rank = 65.18), followed by respondents aged “35 to 44 years old” (average mean rank = 53.94). The respondents aged “below 25 years old” possessed the lowest awareness (average mean rank = 50.92) towards the benefits of drone technology. As previously discussed in subchapter 4.4.2, drone technology is less heard of by the respondents aged “below 25 years old” as compared to the respondents aged between “25 to 34 years old” and “35 to 44 years old”.
Therefore, they perceived the lowest awareness towards the benefits of drone technology. The details on the frequency of hearing about drone technology across the age groups can be referred to Table 4.7.