Socio Technical Plan for an automated weapon detection system con'd
I. Introduction
A socio-technical plan is an
organizational development that deals with the interaction between humans and
technology in workplaces (Long, 2013). Hence, the socio-technical system's
goal is to optimize the organization's social and technical network. Moreover,
the socio-technical plan has rational, semi-rational, and non-rational actors
that affect the organization. Moreover, the socio-technical program helps
produce goods and services for customers as it consists of tools, techniques,
and knowledge. However, managing workgroups, interactions, and complex systems
are easy to operate and rely on the socio-technical plan to consider the
competitive organization and environmental factors. Thus, the optimization of
correlation between the organization and its stakeholders is essential for its
success. Among the fundamental principles of the socio-technical systems
in attaining the organization's goals, adapting to the environment, and
integrating the people's activities, resolve conflicts are critical facts that
the organizations should adopt in their socio-technical system plans. For
academic institutions like Colorado Technical University, the socio-technical system helps address advanced learning and create mechanisms. One of the
technologies applied in a socio-technical program is an automatic weapon
detection system based on artificial intelligence concepts(Alexis, 2009).
II. Scope
A possible automatic weapon detection system that works with AI is
limitless and can be applied in several sectors to protect against violence,
theft, and terrorist activities. The automated weapon detection system is an
artificial intelligence support system that helps to identify people who have
a gun on their body. The application will be designed using python cv and
scanning individuals and detecting the firearm that matches the application
database's gun images. Hence, the more comprehensive the range of the artillery
images stored in the database, the better the application can detect the
weapon.
Teaching:
Weapon detection systems can be used to teach Artificial Intelligence and
Computer Vision within Universities. It can be an excellent example of how a
particular application can integrate images and predict the type of image a
live CCTV camera is showing. In return, send an SMS or call to the responsible
party as part of the notification.
Learning:
Students can use it to practice code and learn how to implement such
applications using python cv or help resolve real-time scenarios.
Creative inquiry:
Such research in an automatic weapon detection system that receives an image from a live camera and scanning a gun holding object is creative in its idea that it can be researched in several aspects of it. It can be an excellent mathematical and scientific example that uses extensive data frames with complex statistical analysis. Hence, it is a perfect example of machine learning visualization techniques as well.
Security:
Implementing an application that could detect a human that carries a gun can
create a favorable environment in the retail and transportation sectors,
including airports, banks, and other industries. Almost every industry can
implement a camera system that detects a weapon by itself and inform the event
to any security personnel without any other human interaction. Hence, the
application can help businesses to be secured and can also save human life. For
instance, a particular robber who enters a store with a gun cannot do anything
as the application can inform the responsible party that someone who holds a
gun is entering the store.
Software:
The software can or might exist in the industry, but its availability is not
enormous. Hence, making such an application that could record a video and
notify is wildly divergent, and there is no standardization implemented for it.
Even if the CCTV cameras are recording, they are not reporting to anyone by
far.
Intellectual property:
The application will increase an intellectual asset for the developer and be a
source of innovation. Due to the application's complexity, it might not be easy
to transfer the intellectual property to any third party.
III. Purpose
The purpose of the study of an automatic weapon detection system between humans
and technology in a socio-technical plan is to accommodate more human needs and
provide a secured environment that facilitates trade, education, peace in
finance, retail industry, transportation, and many others.
V. Supporting forces
Implementing an automated weapons system in the retail, residential, transportation, offices, and financial
sectors will have a bigger impact. Hence, a computerized weapon detection system's
socio-technical plan can be driven by many forces such as technological,
economic, societal, and educational.
Economic forces
Due to the huge demand for security
cameras across all sectors, automated weapon detection systems have a substantial
economic impact. Companies can reduce the cost of security forces around their business
premises using those cameras to scan objects around their compound.
Educational forces
Educational institutions can
eliminate mass shootings in schools using automated weapon detection system
cameras that scan students; the application can notify the responsible party in
advance. Simultaneously, the code is used in implanting a computerized weapon a detection system that uses AI as a means of a case study for student course
projects.
Technological forces
The technology of deep learning in
artificial intelligence will be implemented, and it is one of the advanced
subjects of technological research in artificial research. Hence, the automated
cameras are going to use sophisticated deep learning algorithms. Moreover,
research and development in artificial intelligence and weapon detection systems
are sources of recent technological change.
IV. Challenging Forces
A major challenge is the nature of weapons and the sophistication of new
technologies that bring a new design of weapons; hence, the AI would
face a challenge in identifying the artillery that someone is carrying. Accordingly,
the classification and types of weapons to be defined are hard to imagine and
feed.
V. Methods
The method can be either quantitative analysis using Seaborn code analysis or python pandas to determine the plan's effectiveness and efficiency. Transfer flows and in-depth learning analysis can develop the code and scan weapons from the database's images. The images scanned from the camera will be compared with the pictures stored in the database using deep learning python cv codes. Moreover, a graphical representation of data can be analyzed compared to the fatal rates in each sector and predict how much the future terminal status and analysis and prediction of results can be interpreted.
Classification of images
Neural networks in artificial
intelligence will be detecting and classifying images using supervised and
non-supervised learning algorithms. Neural networks will be trained to
detect knife and pistol as an output. The human who carried a gun or any image that is tagged as a weapon in the system will be seen initially from the
CCTV cameras using a segmentation technique that defines humans from the image's
background.
Image Classification Methods
1. Backend propagation algorithm: a randomly selected image is set for propagation using randomly initialized images to produce an input that is compared to a target vector.
2. Stratified validation: this method helps produce a test of results based on samples in the database and the machine is trained to predict the output based on the stored images.3. Neutral networks for single and multiple class objects: Neural networks use images of single or multiple objects that predict the output based on the input object from the CCTV camera or database.
When it comes to decision-making abilities like brainstorming, inquiry, nominal group technical discussion, and the Delphi method, the Delphi method suits best for the weapon detection system. The Delphi group can be used in analyzing and selecting weapon classification. Images can vary based on the location and nature of the business. Hence, the Delphi method is selected due to the following reasons:
First, a socio-technical plan needs a detailed discussion that can be achieved with a Delphi approach's facilitator role. Second, Delphi's approach also requires skilled members of the discussion group to select the appropriate weapons to be used per sector. Lastly, it is also good that the method and evaluation of the actions can be decided with the best course of action.
VI. Model
Sommerville(2013)
stated that socio-technical architecture consists of layers of software systems. The software systems'
foundation includes the server, LAN, WAN, computers, and other accessories. To
deal with the complexity of business and data management, society, and
organizational relationships, Sommerville(2013) explained with a 7-layer model.
Figure 1: 7 layers of a socio-technical software architecture
When it
comes to an automatic weapon detection system, the application needs a model
that deals with failure propagation. Manage hardware, software, and operator's
reliability manage to help resolve software's if planned accordingly.
Figure 2: Failure Plan
Propagation Model adapted from
To further tune the design and
system propagation in planning an automated weapon detection system socio-technical
plan, the system shall consider technology, organization, and process
flow. Hence, understanding the process,
technology and the organizational processes will reduce the risks, and the associated
problems of developing an automated weapon system will be managed accordingly.
Besides, knowledge and HRM practices are also essential. Fig 2 given below
depicts the dimensions of the socio-technical system adopted from
Figure 3: Socio-Technical System
adopted from Botla
(2018, p. 23).
- Knowledge and management: The Socio-technical system (STS) shall foster understanding inside and outside the organization.
- Competitiveness: STS shall help companies possess a competitive advantage by addressing and planning problems that enhance productivity and support customer value. Having
- Corporate Entrepreneurship: STS shall help to increase the production of new products, processes, and new markets. Innovation shall be erratic and assure successful future design.
- HRM Practices: STS shall help to enhance and create optimum value and HR best practices.
VII. Analytical Plan
The analytical plan can be evaluated
from technological hardware and software architecture perspective, the
automated weapon system software and general application framework.'
Hardware :
The application shall include all
the components like the computers, CCTV cameras, Wi-Fi connected devices, and
hands-on phones to receive a notification.
Software:
The assumption is that the socio-technical plan will give the chance to figure out software that is being used for many
years. Hence, the software's defects and errors will be minimal, and testing of
the software will be integrated. Moreover, the requirement gathering, software
analysis, and design, development, and production support will be flawlessly
executed.
Framework :
The integrated development environment
will help to code and teach as well. The Python framework with the supporting
libraries of NumPy, Pandas, Seaborn, and Matplotlib will be used as a
framework.
Human Interaction :
The decency of the automated weapon detection and associated interaction between the public will be perfectly articulated and an artifact will be recorded entirely for the general public's safety.
VII. Anticipated Results
With the socio-technical plan that can
be implemented in every sector, the automated weapon detection system can be
started in a school system as a model. The reason for selecting the education sector is that the feedback and data can be modified and adjusted, and the
system's limitations can be fixed before it reaches the general industry.
Moreover, once the defects and the limitations of the system are fixed, the
application can be used in any sector. Hence, the results are expected to be
implemented in all industries wherever a CCTV recording camera focuses on where
businesses are happening, and transportation is a sector.
IX. Conclusion
With the application of an artificial intelligence-enabled automated weapon detection system, it is
prominent to see that people and robots' collaboration becomes prominent.
Weapon detection systems are going to eliminate the risk of having an
individual carry a weapon by identifying the person and notifying the
security people in advance. A socio-technical plan on weapon detection can be
another step to impact life by reducing the risk of becoming vulnerable to
terrorist activities or arsonists.
Furthermore, the automated weapon detection system is a change of businesses'
security to another level that guarantees security and reduces fear of random
attacks. Hence, the socio-technical plan will get more benefits and is a game-changer.
However, the socio-technical plan is a big chance of the current CCTV system
that does not notify but recording as well it does not scan who carried what.
Thus, the social-technical plan is something that carries an opportunity for a
change.
In conclusion, the socio-technical plan that deals with an automated weapon detection system will greatly change
technology, society, and the general economy. The challenges are the
integration of the software, resistance from the business and humans in
general.
X. Areas of Future Research
An AI-enabled weapon detection
system is chosen for educational technology for future research. Mimicking human
behavior and understanding the classification of artilleries can help to manage
the work better. Moreover, the automated weapon detection systems developed
with the help of AI can change the current CCTV's that allow an opportunity to
eliminate the use of computers as CCTV cameras can themselves notify whenever
they encounter an individual who carried a weapon.
References
Alexis, M. (2009). Socio-technical systems in ICT: A
comprehensive survey. Retrieved from https://core.ac.uk/download/pdf/150082667.pdf
Botla, L. (2018). Socio-Technical Systems
of a Company: The Dimensionaality of Socio Technical Systems. XI, 24-38.
Long, S. (2013). Socioanalytic methods: discovering the
hidden in organizations and social systems. Karnac Books.
Sommerville, I. (2013). Cs 5032 l3 socio-technical
systems 2013. Retrieved June 08, 2016 from http://www.slideshare.net/sommervi/cs-5032-l3-sociotechnical-systems-2013
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