Make necessary assumptions with justifications about the business and Particulate to incorporate “Voice Recognition” technologies;
Provide a summary of expanding your ICT unit to incorporate “Voice Recognition” technologies;
Provide an initial estimated cost & resource structure with appropriate justifications (using project management software) to meet the organizational needs within the scope to incorporate “Voice Recognition” technologies {cost structure; one page for resource structure; and one page for justification.
Provide a complete project plan (PERT & GANTT Chart), with brief interpretations for non-technical board members;
The project is developed for a major tourist attraction on Australian Highway and the project is to implement Voice Recognition Technology in the same. There are several franchises of the business and the one for which the project is being carried out is a private business that attracts local and international customers from all age groups. There are over 200,000 families that visit the tourist spot annually. The core systems of the tourist spot are in accordance with the latest technology. The Voice Recognition system needs to be integrated in the core system. There is a wireless system implemented in the architecture; however, the system may not be sufficient enough to take higher loads that the business may experience. There are over 1000 employees that may access the system from remote locations.
- The resources required for maintenance of the system post-implementation and the necessary skill set will be available with the organization.
- The technical infrastructure for implementation will require minute enhancements as the core systems are in accordance with the latest technology.
- The security architecture and the policies are in accordance with the Australian standards (Lundy, 2011).
- The end-users will not be resistant towards accepting the voice recognition technology and system in the architecture.
The tourist spot attracts over 200,000 families annually and it would not be possible to assign them with the guides that may explain them about the details of the tourist attraction. Also, there are over 1000 employees associated with the organization. The implementation of voice recognition technology will ensure that the identity management of the resources is done and the details of the tourists can also be saved. The virtual tour of the tourist spot will be made possible as per the voice recognition of the number pronounced by the tourist (Kim et al., 2005). The overall experience for the employees and for the tourists will improve as an outcome.
The proposed model for the Voice Recognition system has been illustrated in the image above. The ICT unit of the tourist attraction does have wireless infrastructure. However, it may not perform adequately with the enhancement in the number of users. The enhancement of the wireless network bandwidth will be needed along with the incorporation of Gigabit router. There are several vendors that may be contracted for the router. CISCO is one such vendor that may provide with the necessary enhancement in the wireless interface and the networking peripherals.
Additionally, database server and application server will be required for the voice recognition technology to be incorporated. A web interface will be needed to allow the end-users to make use of the system. The development tools as Microsoft Visual Studio and design tools as Microsoft Visio and Sketch will be needed. The project will be required to be adequately managed. For this purpose, project management tools, such as Microsoft Project will be necessary.
Assumptions
All of the computer systems and software packages implemented in the tourist attraction will be required to be upgraded with a SoundBlaster 16 or a higher sound card. The recommendation is to make use of a PCI card. Microphones will also be needed to capture the voice samples of the end-users (Yi, 2013).
|
WBS |
Task Name |
Duration |
Cost |
|
1 |
Voice Recognition Technology |
162 days |
$229, 160.00 |
|
1.1 |
Initiation & Planning Phase |
17 days |
$20, 680.00 |
|
1.1.1 |
Analysis of the current ICT infrastructure |
3 days |
$5, 640.00 |
|
1.1.2 |
Definition of aims, objectives, scope |
2 days |
$1, 920.00 |
|
1.1.3 |
Procurement planning and procurement of tools |
8 days |
$7, 360.00 |
|
1.1.4 |
Estimations and resource planning |
3 days |
$2, 880.00 |
|
1.1.5 |
Planning of project areas - quality, communication, risks, stakeholders |
3 days |
$2, 880.00 |
|
1.1.6 |
Milestone 1: Project Plan |
0 days |
$0.00 |
|
1.2 |
Modeling & Algorithms |
44 days |
$59, 840.00 |
|
1.2.1 |
Speech Signal Capture & Endpointing |
6 days |
$5, 280.00 |
|
1.2.2 |
Feature Extraction, Template Matching Algorithm |
6 days |
$5, 280.00 |
|
1.2.3 |
Hidden Markov Model |
6 days |
$10, 560.00 |
|
1.2.4 |
Isolated, continuous, small, and large vocabulary voice recognition considerations |
6 days |
$10, 560.00 |
|
1.2.5 |
Pronunciation & Language Modeling |
8 days |
$14, 080.00 |
|
1.2.6 |
Obtaining multiple results |
8 days |
$14, 080.00 |
|
1.2.7 |
Milestone 2: Modeling & Algorithms |
0 days |
$0.00 |
|
1.3 |
Recognition & Execution |
55 days |
$57, 680.00 |
|
1.3.1 |
Determination of correctness in the recognition results |
10 days |
$9, 200.00 |
|
1.3.2 |
Accuracy and efficiency considerations |
8 days |
$7, 360.00 |
|
1.3.3 |
Training on various models |
8 days |
$14, 080.00 |
|
1.3.4 |
Development of a front end web application for the users |
10 days |
$8, 000.00 |
|
1.3.5 |
Syncing with application and database server |
7 days |
$10, 640.00 |
|
1.3.6 |
Network analysis and infrastructure |
6 days |
$8, 400.00 |
|
1.3.7 |
Milestone 3: Front-end application |
0 days |
$0.00 |
|
1.4 |
Implementation & Control |
31 days |
$79, 760.00 |
|
1.4.1 |
Implementation on the servers |
10 days |
$23, 600.00 |
|
1.4.2 |
Web browser clients |
8 days |
$19, 200.00 |
|
1.4.3 |
Reviews and testing processes |
7 days |
$11, 760.00 |
|
1.4.4 |
Management of the changes |
6 days |
$25, 200.00 |
|
1.4.5 |
Milestone 4: Implementation Results |
0 days |
$0.00 |
|
1.5 |
Closure |
19 days |
$11, 200.00 |
|
1.5.1 |
User Acceptance Testing |
6 days |
$0.00 |
|
1.5.2 |
Performance Measurement |
3 days |
$2, 880.00 |
|
1.5.3 |
Recording of the feedback and its analysis |
4 days |
$3, 840.00 |
|
1.5.4 |
Documentation of the project activities |
6 days |
$3, 840.00 |
|
1.5.5 |
Submission of final report |
1 day |
$640.00 |
|
1.5.6 |
Milestone 5: Final Report |
0 days |
$0.00 |
Estimated Resource Structure
|
WBS |
Task Name |
Duration |
Resource Names |
|
1 |
Voice Recognition Technology |
162 days |
|
|
1.1 |
Initiation & Planning Phase |
17 days |
|
|
1.1.1 |
Analysis of the current ICT infrastructure |
3 days |
Project Manager, Data Scientist |
|
1.1.2 |
Definition of aims, objectives, scope |
2 days |
Project Manager |
|
1.1.3 |
Procurement planning and procurement of tools |
8 days |
Project Manager, Computer Vision Engineer 1 |
|
1.1.4 |
Estimations and resource planning |
3 days |
Project Manager |
|
1.1.5 |
Planning of project areas - quality, communication, risks, stakeholders |
3 days |
Project Manager |
|
1.1.6 |
Milestone 1: Project Plan |
0 days |
|
|
1.2 |
Modeling & Algorithms |
44 days |
|
|
1.2.1 |
Speech Signal Capture & Endpointing |
6 days |
Computer Vision Engineer 1 |
|
1.2.2 |
Feature Extraction, Template Matching Algorithm |
6 days |
Computer Vision Engineer 2 |
|
1.2.3 |
Hidden Markov Model |
6 days |
Computer Vision Engineer 1, Computer Vision Engineer 2 |
|
1.2.4 |
Isolated, continuous, small, and large vocabulary voice recognition considerations |
6 days |
Computer Vision Engineer 1, Computer Vision Engineer 2 |
|
1.2.5 |
Pronunciation & Language Modeling |
8 days |
Computer Vision Engineer 2, Computer Vision Engineer 1 |
|
1.2.6 |
Obtaining multiple results |
8 days |
Computer Vision Engineer 1, Computer Vision Engineer 2 |
|
1.2.7 |
Milestone 2: Modeling & Algorithms |
0 days |
|
|
1.3 |
Recognition & Execution |
55 days |
|
|
1.3.1 |
Determination of correctness in the recognition results |
10 days |
Data Scientist |
|
1.3.2 |
Accuracy and efficiency considerations |
8 days |
Data Scientist |
|
1.3.3 |
Training on various models |
8 days |
Computer Vision Engineer 1, Computer Vision Engineer 2 |
|
1.3.4 |
Development of a front end web application for the users |
10 days |
Web Developer |
|
1.3.5 |
Syncing with application and database server |
7 days |
Database Expert , Technical Analyst |
|
1.3.6 |
Network analysis and infrastructure |
6 days |
Network Specialist, Technical Analyst |
|
1.3.7 |
Milestone 3: Front-end application |
0 days |
|
|
1.4 |
Implementation & Control |
31 days |
|
|
1.4.1 |
Implementation on the servers |
10 days |
Data Scientist , Web Developer, Network Specialist |
|
1.4.2 |
Web browser clients |
8 days |
Computer Vision Engineer 1, Computer Vision Engineer 2, Network Specialist |
|
1.4.3 |
Reviews and testing processes |
7 days |
Data Scientist , Technical Analyst |
|
1.4.4 |
Management of the changes |
6 days |
Computer Vision Engineer 1, Computer Vision Engineer 2, Data Scientist , Database Expert , Technical Analyst |
|
1.4.5 |
Milestone 4: Implementation Results |
0 days |
|
|
1.5 |
Closure |
19 days |
|
|
1.5.1 |
User Acceptance Testing |
6 days |
End-Users |
|
1.5.2 |
Performance Measurement |
3 days |
Project Manager |
|
1.5.3 |
Recording of the feedback and its analysis |
4 days |
Project Manager |
|
1.5.4 |
Documentation of the project activities |
6 days |
Technical Writer |
|
1.5.5 |
Submission of final report |
1 day |
Technical Writer |
|
1.5.6 |
Milestone 5: Final Report |
0 days |
Timesheet and Milestones
|
WBS |
Task Name |
Duration |
Start |
Finish |
Predecessors |
|
1 |
Voice Recognition Technology |
162 days |
Mon 08-10-18 |
Mon 20-05-19 |
|
|
1.1 |
Initiation & Planning Phase |
17 days |
Mon 08-10-18 |
Tue 30-10-18 |
|
|
1.1.1 |
Analysis of the current ICT infrastructure |
3 days |
Mon 08-10-18 |
Wed 10-10-18 |
|
|
1.1.2 |
Definition of aims, objectives, scope |
2 days |
Mon 15-10-18 |
Tue 16-10-18 |
3 |
|
1.1.3 |
Procurement planning and procurement of tools |
8 days |
Wed 17-10-18 |
Tue 30-10-18 |
4 |
|
1.1.4 |
Estimations and resource planning |
3 days |
Wed 17-10-18 |
Fri 19-10-18 |
4 |
|
1.1.5 |
Planning of project areas - quality, communication, risks, stakeholders |
3 days |
Mon 22-10-18 |
Wed 24-10-18 |
6 |
|
1.1.6 |
Milestone 1: Project Plan |
0 days |
Wed 24-10-18 |
Wed 24-10-18 |
7 |
|
1.2 |
Modeling & Algorithms |
44 days |
Thu 25-10-18 |
Mon 24-12-18 |
|
|
1.2.1 |
Speech Signal Capture & Endpointing |
6 days |
Thu 25-10-18 |
Thu 01-11-18 |
8 |
|
1.2.2 |
Feature Extraction, Template Matching Algorithm |
6 days |
Mon 12-11-18 |
Mon 19-11-18 |
10 |
|
1.2.3 |
Hidden Markov Model |
6 days |
Fri 02-11-18 |
Fri 09-11-18 |
10 |
|
1.2.4 |
Isolated, continuous, small, and large vocabulary voice recognition considerations |
6 days |
Mon 26-11-18 |
Mon 03-12-18 |
11 |
|
1.2.5 |
Pronunciation & Language Modeling |
8 days |
Tue 04-12-18 |
Wed 12-12-18 |
13 |
|
1.2.6 |
Obtaining multiple results |
8 days |
Thu 13-12-18 |
Mon 24-12-18 |
14 |
|
1.2.7 |
Milestone 2: Modeling & Algorithms |
0 days |
Mon 24-12-18 |
Mon 24-12-18 |
15 |
|
1.3 |
Recognition & Execution |
55 days |
Tue 25-12-18 |
Mon 11-03-19 |
|
|
1.3.1 |
Determination of correctness in the recognition results |
10 days |
Tue 25-12-18 |
Mon 07-01-19 |
16 |
|
1.3.2 |
Accuracy and efficiency considerations |
8 days |
Tue 08-01-19 |
Thu 17-01-19 |
18 |
|
1.3.3 |
Training on various models |
8 days |
Tue 22-01-19 |
Thu 31-01-19 |
19 |
|
1.3.4 |
Development of a front end web application for the users |
10 days |
Fri 01-02-19 |
Thu 14-02-19 |
20 |
|
1.3.5 |
Syncing with application and database server |
7 days |
Fri 15-02-19 |
Mon 25-02-19 |
21 |
|
1.3.6 |
Network analysis and infrastructure |
6 days |
Mon 04-03-19 |
Mon 11-03-19 |
22 |
|
1.3.7 |
Milestone 3: Front-end application |
0 days |
Mon 11-03-19 |
Mon 11-03-19 |
23 |
|
1.4 |
Implementation & Control |
31 days |
Tue 12-03-19 |
Tue 23-04-19 |
|
|
1.4.1 |
Implementation on the servers |
10 days |
Tue 12-03-19 |
Mon 25-03-19 |
24 |
|
1.4.2 |
Web browser clients |
8 days |
Tue 26-03-19 |
Thu 04-04-19 |
26 |
|
1.4.3 |
Reviews and testing processes |
7 days |
Fri 05-04-19 |
Mon 15-04-19 |
27 |
|
1.4.4 |
Management of the changes |
6 days |
Tue 16-04-19 |
Tue 23-04-19 |
28 |
|
1.4.5 |
Milestone 4: Implementation Results |
0 days |
Tue 23-04-19 |
Tue 23-04-19 |
29 |
|
1.5 |
Closure |
19 days |
Wed 24-04-19 |
Mon 20-05-19 |
|
|
1.5.1 |
User Acceptance Testing |
6 days |
Wed 24-04-19 |
Wed 01-05-19 |
30 |
|
1.5.2 |
Performance Measurement |
3 days |
Wed 08-05-19 |
Fri 10-05-19 |
32 |
|
1.5.3 |
Recording of the feedback and its analysis |
4 days |
Thu 02-05-19 |
Tue 07-05-19 |
32 |
|
1.5.4 |
Documentation of the project activities |
6 days |
Mon 13-05-19 |
Mon 20-05-19 |
33 |
|
1.5.5 |
Submission of final report |
1 day |
Wed 08-05-19 |
Wed 08-05-19 |
34 |
|
1.5.6 |
Milestone 5: Final Report |
0 days |
Mon 20-05-19 |
Mon 20-05-19 |
35 |
The resource and cost structures are justified as these have been estimated and determined using the bottom-up approach and the probable risks are also considered.
The hourly distribution of the project activities and resources is included in the table below followed by the PERT chart and Gantt chart for the project.
|
Task Name |
Work |
|
Voice Recognition Technology |
2,224 hrs |
|
Initiation & Planning Phase |
176 hrs |
|
Analysis of the current ICT infrastructure |
48 hrs |
|
Project Manager |
24 hrs |
|
Data Scientist |
24 hrs |
|
Definition of aims, objectives, scope |
16 hrs |
|
Project Manager |
16 hrs |
|
Procurement planning and procurement of tools |
64 hrs |
|
Project Manager |
32 hrs |
|
Computer Vision Engineer 1 |
32 hrs |
|
Estimations and resource planning |
24 hrs |
|
Project Manager |
24 hrs |
|
Planning of project areas - quality, communication, risks, stakeholders |
24 hrs |
|
Project Manager |
24 hrs |
|
Milestone 1: Project Plan |
0 hrs |
|
Modeling & Algorithms |
544 hrs |
|
Speech Signal Capture & Endpointing |
48 hrs |
|
Computer Vision Engineer 1 |
48 hrs |
|
Feature Extraction, Template Matching Algorithm |
48 hrs |
|
Computer Vision Engineer 2 |
48 hrs |
|
Hidden Markov Model |
96 hrs |
|
Computer Vision Engineer 1 |
48 hrs |
|
Computer Vision Engineer 2 |
48 hrs |
|
Isolated, continuous, small, and large vocabulary voice recognition considerations |
96 hrs |
|
Computer Vision Engineer 1 |
48 hrs |
|
Computer Vision Engineer 2 |
48 hrs |
|
Pronunciation & Language Modeling |
128 hrs |
|
Computer Vision Engineer 1 |
64 hrs |
|
Computer Vision Engineer 2 |
64 hrs |
|
Obtaining multiple results |
128 hrs |
|
Computer Vision Engineer 1 |
64 hrs |
|
Computer Vision Engineer 2 |
64 hrs |
|
Milestone 2: Modeling & Algorithms |
0 hrs |
|
Recognition & Execution |
560 hrs |
|
Determination of correctness in the recognition results |
80 hrs |
|
Data Scientist |
80 hrs |
|
Accuracy and efficiency considerations |
64 hrs |
|
Data Scientist |
64 hrs |
|
Training on various models |
128 hrs |
|
Computer Vision Engineer 1 |
64 hrs |
|
Computer Vision Engineer 2 |
64 hrs |
|
Development of a front end web application for the users |
80 hrs |
|
Web Developer |
80 hrs |
|
Syncing with application and database server |
112 hrs |
|
Database Expert |
56 hrs |
|
Technical Analyst |
56 hrs |
|
Network analysis and infrastructure |
96 hrs |
|
Network Specialist |
48 hrs |
|
Technical Analyst |
48 hrs |
|
Milestone 3: Front-end application |
0 hrs |
|
Implementation & Control |
784 hrs |
|
Implementation on the servers |
240 hrs |
|
Data Scientist |
80 hrs |
|
Web Developer |
80 hrs |
|
Network Specialist |
80 hrs |
|
Web browser clients |
192 hrs |
|
Computer Vision Engineer 1 |
64 hrs |
|
Computer Vision Engineer 2 |
64 hrs |
|
Network Specialist |
64 hrs |
|
Reviews and testing processes |
112 hrs |
|
Data Scientist |
56 hrs |
|
Technical Analyst |
56 hrs |
|
Management of the changes |
240 hrs |
|
Computer Vision Engineer 1 |
48 hrs |
|
Computer Vision Engineer 2 |
48 hrs |
|
Data Scientist |
48 hrs |
|
Database Expert |
48 hrs |
|
Technical Analyst |
48 hrs |
|
Milestone 4: Implementation Results |
0 hrs |
|
Closure |
160 hrs |
|
User Acceptance Testing |
48 hrs |
|
End-Users |
48 hrs |
|
Performance Measurement |
24 hrs |
|
Project Manager |
24 hrs |
|
Recording of the feedback and its analysis |
32 hrs |
|
Project Manager |
32 hrs |
|
Documentation of the project activities |
48 hrs |
|
Technical Writer |
48 hrs |
|
Submission of final report |
8 hrs |
|
Technical Writer |
8 hrs |
|
Milestone 5: Final Report |
0 hrs |
Voice recognition is a concept that recognizes the voice samples of the users and analyses them using language and pronunciation model along with the concepts of machine learning to automate the response of the machine. Pattern recognition and machine learning technologies are involved in the implementation and incorporation of such algorithms. There will be various voice & speech recognitions models and algorithms integrated to make sure that the technology is successfully implemented in the tourist attraction. These will include Speech Signal Capture & Endpointing, Feature Extraction, Template Matching Algorithm, Hidden Markov Mode, Isolated, continuous, small, and large vocabulary voice recognition considerations, Pronunciation & Language Modeling, and obtaining multiple results. There will be certain changes made to the existing ICT units with the procurements and enhancements of networking peripherals, wireless interface, and software packages (Wang, Huang and Yuan, 2011). The enhancement of the wireless network bandwidth will be needed along with the incorporation of Gigabit router. Additionally, database server and application server will be required for the voice recognition technology to be incorporated. A web interface will be needed to allow the end-users to make use of the system. The development tools as Microsoft Visual Studio and design tools as Microsoft Visio and Sketch will be needed. The project will be required to be adequately managed. For this purpose, project management tools, such as Microsoft Project will be necessary (Kim et al., 2004). All of the computer systems and software packages implemented in the tourist attraction will be required to be upgraded with a SoundBlaster 16 or a higher sound card. The recommendation is to make use of a PCI card.
The costs of the projects have been cascaded as per the category of the costs. The internal rate of return that is calculated for the project is 14%.
|
Fiscal Year |
|||||||||||
|
Program Element |
0 |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
|
|
Cost of Voice Recognition Tools |
$19,460 |
||||||||||
|
Modeling and Analysis Costs |
$8,900 |
$8,900 |
$8,900 |
$8,900 |
$8,900 |
$8,900 |
$8,900 |
$8,900 |
$8,900 |
||
|
Cost of Resources |
$5,670 |
$5,670 |
$5,670 |
$5,670 |
$5,670 |
$5,670 |
$5,670 |
$5,670 |
$5,670 |
||
|
Implementation Costs |
$3,800 |
$3,800 |
$3,800 |
$3,800 |
$3,800 |
$3,800 |
$3,800 |
$3,800 |
$3,800 |
||
|
Post-Implementation Costs |
$2,150 |
$2,150 |
$2,150 |
$2,150 |
$2,150 |
$2,150 |
$2,150 |
$2,150 |
$2,150 |
||
|
Management Costs |
$2,780 |
$2,780 |
$2,780 |
$2,780 |
$2,780 |
$2,780 |
$2,780 |
$2,780 |
$2,780 |
||
|
Program Total Costs By Year |
$19,460 |
$23,300 |
$23,300 |
$23,300 |
$23,300 |
$23,300 |
$23,300 |
$23,300 |
$23,300 |
$23,300 |
|
|
Program Grand Total Cost |
$2,29,160 |
Justification
The resulting benefits of the project are as shown below.
|
Fiscal Year |
||||||||||
|
Benefit Sources |
0 |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
|
Increase in the number of tourists visiting annually |
$15,670 |
$15,670 |
$15,670 |
$15,670 |
$15,670 |
$15,670 |
$15,670 |
$15,670 |
$15,670 |
$15,670 |
|
Identity Management & Automation |
$9,990 |
$9,990 |
$9,990 |
$9,990 |
$9,990 |
$9,990 |
$9,990 |
$9,990 |
$9,990 |
$9,990 |
|
Tangible Benefits |
$11,320 |
$11,320 |
$11,320 |
$11,320 |
$11,320 |
$11,320 |
$11,320 |
$11,320 |
$11,320 |
$11,320 |
|
Intangible Benefits |
$10,660 |
$10,660 |
$10,660 |
$10,660 |
$10,660 |
$10,660 |
$10,660 |
$10,660 |
$10,660 |
$10,660 |
|
Total Benefits Per Year |
$47,640 |
$47,640 |
$47,640 |
$47,640 |
$47,640 |
$47,640 |
$47,640 |
$47,640 |
$47,640 |
$47,640 |
|
Confidence Factor |
38% |
44% |
50% |
56% |
62% |
70% |
78% |
80% |
82% |
|
|
Benefits Claimed for Analysis |
$0 |
$18,103 |
$20,962 |
$23,820 |
$26,678 |
$29,537 |
$33,348 |
$37,159 |
$38,112 |
$39,065 |
|
Program Grand Total Benefit |
$2,66,784 |
The cost-benefit analysis is as shown below with 8% discount factor applied.
|
Fiscal Year |
||||||||||
|
0 |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
|
|
Undiscounted Flows |
||||||||||
|
Costs |
-$19,460 |
-$23,300 |
-$23,300 |
-$23,300 |
-$23,300 |
-$23,300 |
-$23,300 |
-$23,300 |
-$23,300 |
-$23,300 |
|
Benefits |
$0 |
$18,103 |
$20,962 |
$23,820 |
$26,678 |
$29,537 |
$33,348 |
$37,159 |
$38,112 |
$39,065 |
|
Net Cash Flow |
-$19,460 |
-$5,197 |
-$2,338 |
$520 |
$3,378 |
$6,237 |
$10,048 |
$13,859 |
$14,812 |
$15,765 |
|
Discount Factors |
||||||||||
|
Discount Rate |
8.0% |
|||||||||
|
Base Year |
0 |
|||||||||
|
Year Index |
0 |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
|
Discount Factor |
1.0000 |
0.9259 |
0.8573 |
0.7938 |
0.7350 |
0.6806 |
0.6302 |
0.5835 |
0.5403 |
0.5002 |
|
Discounted Flows |
||||||||||
|
Costs |
-$19,460 |
-$21,574 |
-$19,976 |
-$18,496 |
-$17,126 |
-$15,858 |
-$14,683 |
-$13,595 |
-$12,588 |
-$11,656 |
|
Benefits |
$0 |
$16,762 |
$17,971 |
$18,909 |
$19,609 |
$20,102 |
$21,015 |
$21,682 |
$20,591 |
$19,542 |
|
Net |
-$19,460 |
-$4,812 |
-$2,005 |
$413 |
$2,483 |
$4,245 |
$6,332 |
$8,087 |
$8,002 |
$7,886 |
|
Cumulative |
-$19,460 |
-$24,272 |
-$26,277 |
-$25,864 |
-$23,381 |
-$19,136 |
-$12,804 |
-$4,717 |
$3,285 |
$11,171 |
|
Net Present Value |
$11,171 |
|||||||||
|
Internal Rate of Return |
14% |
It is recommended that project that is carried out is managed with the approach as a combination of agile and Project Management Body of Knowledge (PMBoK) methodologies. There will be various risks and implementation issues that may come up in the process that will be avoided as a result.
The PMBoK management approach shall focus upon the initiation, planning, and closure phases. The initiation and planning activities shall include Analysis of the current ICT infrastructure, Definition of aims, objectives, scope, Procurement planning and procurement of tools, Estimations and resource planning, and Planning of project areas - quality, communication, risks, stakeholders. The use of PMBoK methodology will provide the management with the guidelines on managing each of these areas effectively (Zwikael, 2009).
The modelling, analysis, execution, and implementation phases shall be managed using the agile methodology for project management. These will include Speech Signal Capture & Endpointing, Feature Extraction, Template Matching Algorithm, Hidden Markov Mode, Isolated, continuous, small, and large vocabulary voice recognition considerations, Pronunciation & Language Modeling, and obtaining multiple results. There will be certain changes made to the existing ICT units with the procurements and enhancements of networking peripherals, wireless interface, and software packages (Juricek, 2014). The execution and implementation processes will cover Determination of correctness in the recognition results, Accuracy and efficiency considerations, Training on various models, Development of a front end web application for the users, Syncing with application and database server, and Network analysis and infrastructure. Implementation tasks will include implementation on the servers, Web browser clients, Reviews and testing processes, and Management of the changes. The use of the agile methodology will make sure that these processes are flexible and scalable in nature (Indelicato, 2016).
There shall be use of meetings and active communication during the entire project timeline to avoid any issues and conflicts during the project timeline.
|
WBS |
Task Name |
Duration |
Start |
Finish |
Predecessors |
Resource Names |
Cost |
|
1.4 |
Implementation & Control |
31 days |
Tue 12-03-19 |
Tue 23-04-19 |
$79,760.00 |
||
|
1.4.1 |
Implementation on the servers |
10 days |
Tue 12-03-19 |
Mon 25-03-19 |
24 |
Data Scientist ,Web Developer, Network Specialist |
$23,600.00 |
|
1.4.2 |
Web browser clients |
8 days |
Tue 26-03-19 |
Thu 04-04-19 |
26 |
Computer Vision Engineer 1,Computer Vision Engineer 2,Network Specialist |
$19,200.00 |
|
1.4.3 |
Reviews and testing processes |
7 days |
Fri 05-04-19 |
Mon 15-04-19 |
27 |
Data Scientist ,Technical Analyst |
$11,760.00 |
|
1.4.4 |
Management of the changes |
6 days |
Tue 16-04-19 |
Tue 23-04-19 |
28 |
Computer Vision Engineer 1,Computer Vision Engineer 2,Data Scientist ,Database Expert ,Technical Analyst |
$25,200.00 |
|
1.4.5 |
Milestone 4: Implementation Results |
0 days |
Tue 23-04-19 |
Tue 23-04-19 |
29 |
$0.00 |
The post-implementation plan of the project shall focus upon the maintenance cycles, support activities, feedback and improvement activities.
There may be risks to security architecture with the passage of time. A regular security and vulnerability assessment shall be done as a part of post-implementation project activities. The management of security incidents shall be done with system updates and installation of the patches. Incident record and response system shall also be implemented to handle the user issues. The customer support activities shall be carried out so that the customer queries are resolved. There will be feedback process integrated with the voice recognition system. The feedback process shall be integrated with the improvement activities which shall be analysed by the quality assurance team. The changes shall be made to the project accordingly (Kobylanska, 2017).
Expansion of ICT Units
The post-implementation project activities shall be managed by the use of management methodologies as agile methodology for project management and PMBoK methodology.
Recommendations & Conclusion
The Voice Recognition Technology that is being incorporated in the tourist attraction of Australia shall be managed and maintained using PMBoK and agile methodologies. It is recommended that quality assurance and quality control activities, such as reviews, inspections, functional testing, security testing, performance testing, and regression testing are carried out on the system throughout the lifecycle of the project.
Voice recognition is a concept that recognizes the voice samples of the users and analyses them using language and pronunciation model along with the concepts of machine learning to automate the response of the machine. Pattern recognition and machine learning technologies are involved in the implementation and incorporation of such algorithms. There shall be various voice & speech recognitions models and algorithms integrated to make sure that the technology is successfully implemented in the tourist attraction. The enhancement of the wireless network bandwidth will be needed along with the incorporation of Gigabit router. There are several vendors that may be contracted for the router. CISCO is one such vendor that may provide with the necessary enhancement in the wireless interface and the networking peripherals. All of the computer systems and software packages implemented in the tourist attraction will be required to be upgraded with a SoundBlaster 16 or a higher sound card. The recommendation is to make use of a PCI card. Microphones will also be needed to capture the voice samples of the end-users.
References
Indelicato, G. (2016). Agile for Project Managers. Project Management Journal, 47(1), pp.e4-e4.
Juricek, J. (2014). Agile Project Management Principles. Lecture Notes on Software Engineering, pp.172-175.
Kim, J., Kang, S., Ryu, H. and Lee, S. (2004). A Study on Design and Implementation of Embedded System for speech Recognition Process. Journal of Korean Institute of Intelligent Systems, 14(2), pp.201-206.
Kim, L., Kang, S., Ryu, H., Jang, W., Lee, S. and Pandya, A. (2005). Design and Implementation of Artificial Intelligent Motorized Wheelchair System using Speech Recognition and Joystick. Control and Intelligent Systems, 33(2).
Kobylanska, M. (2017). Creating demand for the tourist product during the implementation of geotourist project for post-mining objects. Acta Geoturistica, 8(2), pp.58-66.
Kumar, D., Sachan, A. and Kumar, M. (2014). Implementation of Speech Recognition in Web Application for Sub Continental Language. International Journal of Engineering Trends and Technology, 9(11), pp.572-575.
Lundy, D. (2011). Do We Need Board Specialty Recognition (BRS) in Voice and Voice Disorders?. Perspectives on Voice and Voice Disorders, 21(2), p.40.
Wang, S., Huang, S. and Yuan, F. (2011). Design and Implementation of Speech Recognition System Based on SPCE061A. Advanced Materials Research, 187, pp.389-393.
Yi, B. (2013). Design and Implementation of Speech Recognition System Based on FPGA. Applied Mechanics and Materials, 416-417, pp.1156-1159.
Zwikael, O. (2009). The Relative Importance of the PMBOK® Guide's Nine Knowledge Areas during Project Planning. Project Management Journal, 40(4), pp.94-103.
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