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

The implementation of an automated weapons system in the retail, residential, transportation, offices, and financial sectors has a bigger impact. Hence, the socio-technical plan of an automated weapon detection system 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 huge 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 new technological change.

 VI. Challenging Forces

             The 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.

 VII. Methods

 

            The method can be either quantitative analysis using Seaborn code analysis or python pandas to determine the plans' effectiveness and efficiency. Transfer flow and in-depth learning analysis can develop code and scan weapons from images stored in the database. 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.

 

 

 References

 

Alexis, M. (2009). Socio-technical systems in ICT: A comprehensive survey. Retrieved from https://core.ac.uk/download/pdf/150082667.pdf

Long, S. (2013). Socioanalytic methods: discovering the hidden in organizations and social systems. Karnac Books.

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