Carrying out the dangerous and varied duties and missions of the police in order to establish order and security in the society has created challenges for the police with traditional methods and created serious dangers in the cultural, economic, social, security, etc. fields. brought police, as the custodian of public security and one of the pillars of national security, should apply preventive measures in dealing with crimes, and by making changes in various areas of the organization, such as structural, technological, process and mission areas, it can establish security in the society. Intelligence is an approach that can solve the needs of the police in mission and service areas. In order to enrich the activities of making the police Smarter, it is necessary to pay attention to the scientific foundations as the focus of the activities, and for this purpose, the strategic model of the Smart police is needed to organize the activities and systematize the actions, so that all the programs and priorities of the organization Compile and implement according to the strategic model. This research was done by using analytical studies and literature on the subject to examine the four objectives of SWOT (threats, opportunities, strengths and weaknesses). It was prioritized using the Hierarchical Process (AHP) method. The statistical population of the research included experts and experts related to faraja intelligence, and 15 of these experts were selected to answer the questions using the purposeful sampling method. SWOT-AHP method and expert choice software were used to check the information. The findings showed that the existence of technical capabilities (data infrastructure, database, data governance, etc.) is considered a strength for the planning and strategy of Smart police, and data analysis for the scientific discovery of crimes is one of the opportunities for the strategic model of Smart police.

Background and purpose: Smart Plus can play an effective role in crime prevention by providing timely services using technology. Establishing Smart police requires knowing the internal and external factors of the organization and providing the necessary strategies. Therefore, the aim of the current research is to provide strategies for deploying Smart police in crime prevention. Method: The current applied research has a descriptive-analytical nature and from the point of view of the data collection method, it is a mixed research (qualitative and quantitative). The study population in the qualitative section, including university professors and crime prevention elites, were selected in a purposeful method based on criteria. Data were collected using semi-structured interviews and after each interview, its text was implemented and basic themes were extracted. The data reached saturation in the 18th person. The credibility of the data was confirmed by the descriptive method and its reliability was confirmed by receiving the opinions of two other coders who were familiar with the subject and making their desired corrections in the triangulation process and analyzed by thematic analysis method. The results of the qualitative part were used to make tools in the quantitative part. The statistical population of the quantitative part was formed by senior and executive managers of the prevention police, which was determined by a simple random method and based on Cochran's formula, and the data were collected using a questionnaire. The validity of the tool was determined by the formal method and its reliability was determined with Cronbach's alpha of 0. 82, and then the data was analyzed with the SWAT technique to achieve analysis. Findings: Based on the findings of the research based on environmental science, in the qualitative part, four factors including weaknesses, threats, strengths and opportunities were identified in the internal and external environment of the police organization. In the quantitative part, the results showed that "using supporting strategies" and "having a long-term plan and defining the vision" with a final score of 0. 226 and 0. 222 as the most important strengths and "public trust in the police" with a final score of 196. 0 is considered as the most important opportunity. Also, the position of the police organization is in the aggressive area according to internal and external factors and quantitative analysis. Conclusion: The results indicate that building trust and increasing public trust in the police by using the forward-looking thinking of police managers and commanders is the first priority of an aggressive strategy, and adopting this strategy and implementing it can facilitate the speed and process of establishing a Smart police. . Therefore, there are better conditions for the establishment of Smart police in crime prevention, but in a comprehensive and systemic approach, all implementation plans to realize the four strategies should be given practical attention.  

Background and aim: The virtual space, as a product of information technology, has led to the migration of a significant portion of crimes from the physical realm to the virtual realm. The scope and impact of virtual crimes are much broader and deeper than physical crimes. Therefore, the Command Headquarters of Law Enforcement Forces of the Islamic Republic of Iran, as a technology-oriented organization, needs to move towards becoming an intelligent organization, specifically Smart police, and achieving this goal without a suitable model and strategy is challenging. Accordingly, the aim of this research is to design the Smart police model in the Command Headquarters of Law Enforcement Forces of the Islamic Republic of Iran.Method: This study is applied research and qualitatively based in terms of methodology. The research population consists of experts in the field of information technology and management within and outside the organization. Using purposive sampling and based on theoretical saturation principle, 18 individuals were selected as the sample, and semi-structured interviews were conducted with them. Content analysis was used to analyze the data.Results: By implementing the interviews and coding the participants' responses, the researchers focused on explaining the concepts and dimensions. Through content analysis of the interviews, 61 indicators and 17 sub-concepts (components) were obtained, which ultimately fell into four main dimensions ("employees," "process," "technology," and "structure").Conclusion: The realization of the Smart police model depends on strategic planning for the four dimensions of "employees," "process," "technology," and "structure," along with the 17 components and 61 indicators. The employment and coordination of these dimensions, components, and indicators play a fundamental role in achieving the Smart police model.

Background and aim:  The use of artificial intelligence in intelligence and security missions-due to its capabilities in big data analysis, threat prediction, and decision support-is rapidly expanding. This study aims to present a framework for utilizing AI in Smart police security missions. Method:  This applied research employs a mixed-methods approach (qualitative-quantitative). Qualitative data were collected through interviews with 10 AI and security experts and analyzed using thematic analysis. Based on qualitative findings, a researcher-made questionnaire was designed and distributed to 29 expert specialists for quantitative analysis. Quantitative data were analyzed using SPSS software, with instrument validity confirmed by Cronbach's alpha coefficient (0. 91). Results:  Results identify three main dimensions in AI utilization: Requirements and prerequisites (58% importance, 3 components, 9 indicators),Legal and protective requirements (24% importance, 4 components, 11 indicators),AI-based services (18% importance, 4 components, 10 indicators)Conclusion:  The findings demonstrate that optimizing AI use in police security missions requires comprehensive design and implementation of service dimensions/components, strengthening mechanisms, and legal requirements. These measures can significantly enhance the efficiency and effectiveness of intelligence and security missions while helping effectively counter emerging threats.

Recently, the use of information and communication technology have very important role in Smartening cities and the police. With the development of the internet of things and the Smart city, the ability to easily access high-reliability communications and provide a platform for fast coverage and connectivity is becoming a vital need for the next generation of wireless telecommunications systems. UAVs play an important role in providing timely and necessary wireless communication services for public safety applications, Smart city, Smart police and to recover services immediately after disasters. Collaboration between UAVs and communications infrastructure is able to support public safety requirements such as immediate analysis, immediate monitoring and advanced decision-making to help Smart cities meet their public safety needs. Therefore, the deployment of UAV-based wireless communications can save individuals and ecosystems in an efficient way by helping public safety organizations deal with threats and disaster management. In this paper, the types of UAVs and their characteristics have been investigated, then, the benefits of their use for public safety and Smart police applications are outlined. In the following, the various applications of UAVs in different aspects of Smart cities, Smart police, military and disaster management and next-generation cellular telecommunication networks have been discussed. The benefits, limitations, telecommunication and security challenges of these systems have also been addressed.

Currently, different types of crimes have occurred in the country's geographical area. As a leading organization at any given moment, the police have produced data that will need to be processed quickly and analyzed to be used in missions. This requires an intelligent mechanism that cannot be exploited without the use of machine capacities. Increasing hardware and software equipment in an organization will lead to energy consumption. With a view to a clean, wireless, and cordless environment and permanent connection of systems and their stability, wireless power transfer (WPT)technology is the best option for wirelessly charging of electronic equipment. All missions, hardware are charged wirelessly, and system outages do not disrupt operations. To make the police intelligent, all kinds of electronic equipment available at the border, corridor, and police station, etc., can be equipped with wireless power transmission technology, eliminating cables and the ability to charge remotely. The research has been applied in terms of purpose and by simulation method. Since the transmitter efficiency depends on the precise design of the amplifier section, in this paper, the Class E power amplifier is designed at a frequency of 145 MHz. It is obtained in the ADS simulation software, and the efficiency is 2. 77. The analysis shows that this technology can be used in places And various police missions charged the equipment permanently.

. For integrated management and command and control over situations and issuing appropriate orders, it is necessary for an organization like the police to intelligently monitor all issues and create an intelligent command and control center to complete missions efficiently. One of the components of increasing security is people's cooperation with the police in order to scientifically detect crimes, as well as benefiting from the latest technologies at the organization level. Despite the wide role of information technology in Faraja, in order for Faraja to carry out the assigned missions and establish order and security, the police organization must be transformed from a technology-oriented to a Smart police, so the purpose of this research is to "provide a model It is a native strategy of the Smart police of the Islamic Republic of Iran. This research is applied-developmental in terms of type and descriptive-analytical in terms of method. The statistical population of this research is targeted among the experts whose common feature is management experience in Smart projects, with expertise in the fields of systems design or information technology, a strategic job position, which is estimated at 50 people. The analysis of the information and data obtained from the study of the sources has been done in a qualitative way and the information obtained from the questionnaire has been analyzed using the method of structural equations with the partial least squares approach and the use of SmartPLS software.

Distributed Denial of Service (DDoS) attack is an attempt to make network resources inaccessible to legitimate users. Today, the number of DDoS attacks is increasing rapidly, this is a threat to Internet users, and police networks are no exception to this threat and are more sensitive due to the constant need for these networks to respond to legal requests. Although the target of DDoS attacks may be different, they generally try to temporarily or permanently disable the services of a victim server connected to the Internet. In this paper, a network layer-based method independent from communication protocols is presented that is able to detect attack behaviors without the need to know normal network behaviors. In addition, this method does not need to store large volumes of profiles, multiple lists and attack signatures. This method is done in three steps: feature extraction through a two-dimensional wavelet decomposition that provides the energy distribution diagram, detection of the change point with the help of fuzzy logic rules and deep neural network analysis as the final step of detection. The proposed method was investigated on VAST and ISCX datasets in which it was able to detect DDoS attacks in 10-second periods with 99. 99% accuracy for VAST dataset and 99. 08% accuracy for ISCX dataset.

The development and use of artificial intelligence methods to solve different problems have been a vast and active research field for many years. The problem of pursuit-evasion has been used as a testbed in much new research on machine learning and artificial intelligence. In this research, as a specific form of the pursuit-evasion problem, some pursuer agents pursue a fugitive agent. The objective of the study is to train two intelligent pursuer agents using deep Q networks so that they can return the fugitive agent to a specific position in the shortest possible time. Two models were presented using the mentioned algorithm in two different scenarios to learn from the experiences of the pursuer agents and finally the performance of the proposed models was tested and evaluated by comparison with the exact brute force algorithm. After training the agents, it was observed that in both scenarios, the cost of the networks gradually decreased and the amount of rewards received by the pursuer agents at the end of the training increased and converged to certain values. It was observed that the pursuer agents are completely successful in returning the fugitive agent to the specific position and in the second scenario, in more than 90% of random environments, they perform this operation successfully.

Background and objectives: Managers in the field of research need the ability to make quick, accurate and intelligent decisions to maintain the survival of the university in competition with other universities. Assessing the Smartness position of the research center helps the university to prepare itself for the successful implementation of the university's Smart-making based on the obtained results and then to invest in such a serious and important activity. This study sought to assess the maturity of Smart-making in the research center in Amin police University. Methodology: The approach of this research is a combination of qualitative and quantitative approaches. In terms of its objectives this study is of an applied research type and in terms of its method it is considered as a descriptive-analytical study. The statistical population consists of information technology and research experts from research centers of other universities and I. R. I police. This research has been conducted in three stages: 1-Extraction of Smart-making assessment components through nominal group method and Delphi validation method, 2-Selection of the best basic model of maturity assessment through systematic literature review and in a quantitative part through two test methods of "Chi-square" and "weighted sum" methods using questionnaire tools and SPSS and Expert choice software, and 3-Assessing the Smartness maturity of the research center through a questionnaire tool. Findings: The University's research center covers 57. 14% of the second level of maturity, 55. 55% of the third level of maturity, 90. 32% of the fourth level of maturity and 58. 33% of the fifth level of Smartness maturity. Results: To increase productivity, it is necessary to put the activities of the organization in a targeted direction. The most calculated gap was related to the indicators of the third level of maturity and in the fourth level of maturity in favorable conditions. The dashboard presented in this research gives managers and decision makers of organizations a clear view of the status quo of the organization and a view to the future and the situation.