scholarly journals Artificial Intelligence for marketing plan: the case for e-marketing companies

2021 ◽  
pp. 81-95
Author(s):  
Abeer Elsayed Fayed
Keyword(s):  
Artificial Intelligence ◽  
The Internet ◽  
Marketing Plan ◽  
Great Ability ◽  
Scientific Discussion ◽  
Logical Sequence ◽  
Stratified Sample ◽  
Strategic Goals ◽  
Research Goal ◽  
And Control

This paper summarises the arguments and counterarguments within the scientific discussion on artificial intelligence (AI) in preparing a marketing plan for e-marketing organizations. This research aims to identify the extent of the contribution of AI in preparing the marketing plan. The author noted that intended to know how e-marketing companies could use AI techniques in situation analysis, analyze competitors' strategies, strategic goals, preparing marketing strategies, preparing an estimated marketing budget, and control a marketing plan. Systematization of the scientific background and approaches on preparing a marketing plan for e-marketing organizations indicates that many companies, especially small companies, marketing their products via the Internet, cannot develop a successful marketing plan. In turn, it could be solved through the use of AI techniques. The study was conducted on a group of companies that market their products via the Internet in the Kingdom of Saudi Arabia. To gain the research goal, this study was carried out in the following logical sequence: 1) developing the stratified sample by collecting statistical information for 141 company in a variety of fields; 2) analyzing the data using SPSS; 3) predicting how AI could be used in preparing the marketing plan; 4) identifying the arrangement of the steps for preparing the marketing plan in terms of the ability of AI techniques. The methodological tools of the study were methods of the multiple regression analysis and the Friedman test. The study empirically confirms and theoretically proves that AI contributes significantly in developing marketing plans through its great contribution to environmental analysis and analysis of competitors' strategies and setting marketing goals. Besides, AI contributes to preparing the budget and appreciating the marketing plan, to its evaluation and control. The author mentioned that AI provides understanding and selecting target markets and sectors, targeting customers, and preparing appropriate marketing mix strategies for each market sector. Therefore, the study provides recommendations to online organizations to use AI in preparing their marketing plan because of its great ability to contribute to this.

scholarly journals Management of Software-Defined Networking Powered by Artificial Intelligence

2021 ◽  
Author(s):  
Jehad Ali ◽  
Byeong-hee Roh
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Internet Of Things ◽  
Heterogeneous Networks ◽  
Software Defined Networking ◽  
Machine Learning Algorithms ◽  
The Internet ◽  
Underlying Network ◽  
And Control ◽  
The Internet Of Things

Separating data and control planes by Software-Defined Networking (SDN) not only handles networks centrally and smartly. However, through implementing innovative protocols by centralized controllers, it also contributes flexibility to computer networks. The Internet-of-Things (IoT) and the implementation of 5G have increased the number of heterogeneous connected devices, creating a huge amount of data. Hence, the incorporation of Artificial Intelligence (AI) and Machine Learning is significant. Thanks to SDN controllers, which are programmable and versatile enough to incorporate machine learning algorithms to handle the underlying networks while keeping the network abstracted from controller applications. In this chapter, a software-defined networking management system powered by AI (SDNMS-PAI) is proposed for end-to-end (E2E) heterogeneous networks. By applying artificial intelligence to the controller, we will demonstrate this regarding E2E resource management. SDNMS-PAI provides an architecture with a global view of the underlying network and manages the E2E heterogeneous networks with AI learning.

scholarly journals Approaches Based on Artificial Intelligence and the Internet of Intelligent Things to Prevent the Spread of COVID-19: Scoping Review (Preprint)

2020 ◽  
Author(s):  
Aya Sedky Adly ◽  
Afnan Sedky Adly ◽  
Mahmoud Sedky Adly
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Resource Allocation ◽  
Modeling And Simulation ◽  
Large Scale ◽  
Information Gathering ◽  
The Internet ◽  
Experimental Therapies ◽  
Computer Scientists ◽  
And Control

BACKGROUND Artificial intelligence (AI) and the Internet of Intelligent Things (IIoT) are promising technologies to prevent the concerningly rapid spread of coronavirus disease (COVID-19) and to maximize safety during the pandemic. With the exponential increase in the number of COVID-19 patients, it is highly possible that physicians and health care workers will not be able to treat all cases. Thus, computer scientists can contribute to the fight against COVID-19 by introducing more intelligent solutions to achieve rapid control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes the disease. OBJECTIVE The objectives of this review were to analyze the current literature, discuss the applicability of reported ideas for using AI to prevent and control COVID-19, and build a comprehensive view of how current systems may be useful in particular areas. This may be of great help to many health care administrators, computer scientists, and policy makers worldwide. METHODS We conducted an electronic search of articles in the MEDLINE, Google Scholar, Embase, and Web of Knowledge databases to formulate a comprehensive review that summarizes different categories of the most recently reported AI-based approaches to prevent and control the spread of COVID-19. RESULTS Our search identified the 10 most recent AI approaches that were suggested to provide the best solutions for maximizing safety and preventing the spread of COVID-19. These approaches included detection of suspected cases, large-scale screening, monitoring, interactions with experimental therapies, pneumonia screening, use of the IIoT for data and information gathering and integration, resource allocation, predictions, modeling and simulation, and robotics for medical quarantine. CONCLUSIONS We found few or almost no studies regarding the use of AI to examine COVID-19 interactions with experimental therapies, the use of AI for resource allocation to COVID-19 patients, or the use of AI and the IIoT for COVID-19 data and information gathering/integration. Moreover, the adoption of other approaches, including use of AI for COVID-19 prediction, use of AI for COVID-19 modeling and simulation, and use of AI robotics for medical quarantine, should be further emphasized by researchers because these important approaches lack sufficient numbers of studies. Therefore, we recommend that computer scientists focus on these approaches, which are still not being adequately addressed.

Forecasting the number of incoming tourists using Arima model: case study from Armenia

2021 ◽  
Vol 5 (3) ◽  
pp. 139-148
Author(s):  
Gayane Tovmasyan
Keyword(s):  
Arima Model ◽  
Tourism Demand ◽  
Model Case ◽  
Scientific Discussion ◽  
Logical Sequence ◽  
Research Goal ◽  
The Republic ◽  
Flight Cancellations ◽  
Strategic Policies

This paper summarizes the arguments and counterarguments within the scientific discussion on the issue of forecasting tourism demand and touristic flows. During COVID-19 tourism sphere suffered a lot in the whole world. Many countries try to do forecasts and make recovery plans for tourism. Tourism has been a growing sphere in Armenia in recent years. However, the number of incoming tourists decreased by 80 percent because of the pandemic. The main purpose of the research is to forecast tourism demand in the Republic of Armenia. Systematization of scientific sources and approaches for solving the problem identified many methods and models for doing forecasts. The variables used to depend on the method selected. For gaining the research goal, the study was carried out in the following logical sequence: 1) discussion on some literature sources; 2) analysis of the current situation of tourism in Armenia; 3) interpretation of forecast results; 4) providing some recommendations. The methodological tool of the research was mainly the ARIMA method. The data rest on the publications of the Statistical Committee of the Republic of Armenia. Time series for the number of incoming tourists include from 2001-Q1 till 2019-Q4 data. 2020 was not included in the model, as there was a sharp decline. Besides, in the second quarter of 2020, there were no tourists at all because of restrictions and flight cancellations. The obtained data show that if there were no pandemic, the number of incoming tourists would increase on average by 12.81% in 2021, 13.42% – in 2022, and 13.66% – in 2023. The results are realistic. The tourism sphere is expected to grow in 2021. This paper suggested some steps for recovering and restoring tourism, particularly by using aggressive marketing strategies, word-of-mouth, influencer marketing, etc. The research results could be useful for state organs of the sphere to forecast their strategic policies. The applied approach and suggestions may be helpful in many countries which try to restart tourism after the pandemic.

scholarly journals Research on Mobile Communication Technology in the Internet+ Era

2021 ◽  
Vol 3 (1) ◽  
pp. 9
Author(s):  
Shuxu Cao
Keyword(s):  
Artificial Intelligence ◽  
Communication Technology ◽  
Mobile Communication ◽  
Mobile Communications ◽  
Science And Technology ◽  
The Internet ◽  
Contact Method ◽  
Mobile Communication Technology ◽  
And Control ◽  
Intelligence Science

<p>With the continuous development of science and technology, although artificial intelligence has become the norm, if artificial intelligence science and technology are applied to mobile communications, it will be a huge technological leap. Some companies use artificial intelligence to analyze their faults and early warnings, so that they can effectively communicate between communications. This kind of contact method mainly relies on the analysis of personnel, and finds out the cause of the fault through network positioning, so as to realize the connection between the networks and the early warning of the communication network. By building system equipment to realize remote operation and control support communication, communication can be effectively realized.</p>

scholarly journals Criminal Policy for Crimes Committed Using Artificial Intelligence Technologies: State, Problems, Prospects

2020 ◽  
pp. 116-122
Author(s):  
Alexander P. Sukhodolov ◽  
Artur V. Bychkov, ◽  
Anna M. Bychkova
Keyword(s):  
Artificial Intelligence ◽  
Criminal Liability ◽  
Autonomous Systems ◽  
Criminal Policy ◽  
New Variety ◽  
Scientific Discussion ◽  
The Subject ◽  
And Control ◽  
Self Learning ◽  
Technological Platforms

The aim of the work is to study the criminal policy in relation to crimes committed using technologies based on artificial intelligence algorithms. The varieties of these crimes are described: phishing, the use of drones, the synthesis of fake information, attacks through automated autonomous systems and bots. Given the fact that artificial intelligence technologies are capable of self-learning and independent actions without direct human intervention and control, the key issue in the criminal policy regarding crimes committed using artificial intelligence algorithms is the question of the subject of criminal liability. The concepts existing in official documents and scientific literature are analyzed on this issue, in the development of scientific discussion, it is proposed to update the legal construction of “innocent harm”. The prospects of criminal policy in this direction are indicated in the creation of a fundamentally new variety of blanket norms: from “law as a text” to “law as a code” and its implementation by technological platforms

Internet of Things based Automation using Artificial Intelligence

2018 ◽  
Vol 6 (7) ◽  
pp. 142
Author(s):  
Chandra Sekar B ◽  
Nikhil K S ◽  
Raju K N ◽  
Sanjay M ◽  
Chandrappa D N
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Smart Cities ◽  
The Internet ◽  
Home Automation ◽  
Web Page ◽  
Ip Address ◽  
And Control ◽  
The Internet Of Things ◽  
Exchange Data

The  Internet of Things(IoT)  has become a hot topic in the present tech-driven world. Internet of Things is one of the promising technology used to control objects connected to Internet through IP address, which enables objects to collect and exchange data. Internet of Things is expanding itself into different areas. Home Automation is one of the trend in application of IoT for realizing smart cities. In the paper, we are developing a system which will control through MQTT protocol. MQTT has been utilized as a platform to provide IoT services which will monitor the applications and generate alerts or take intelligent decisions using concept of IoT. Nodemcu was used as aIoT end device connecting relays to the platform via wifi channel. Home scenario is created and designed IoT messages satisfying the scenario requirement. We also implemented Automation through HTML web page. A main contribution of this paper is that it summarizes uses of Intenet of Things in Home Automation with Artificial Intelligence to monitor and control the appliances.

scholarly journals Mapping the Role of Digital Health Technologies in Prevention and Control of COVID-19 Pandemic: Review of the Literature

2021 ◽  
Vol 30 (01) ◽  
pp. 026-037
Author(s):  
Binyam Tilahun ◽  
Kassahun Dessie Gashu ◽  
Zeleke Abebaw Mekonnen ◽  
Berhanu Fikadie Endehabtu ◽  
Dessie Abebaw Angaw
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Prevention And Control ◽  
Digital Health ◽  
The Internet ◽  
Health Technologies ◽  
And Control ◽  
The Internet Of Things

Summary Background: Coronavirus Disease (COVID-19) is currently spreading exponentially around the globe. Various digital health technologies are currently being used as weapons in the fight against the pandemic in different ways by countries. The main objective of this review is to explore the role of digital health technologies in the fight against the COVID-19 pandemic and address the gaps in the use of these technologies for tackling the pandemic. Methods: We conducted a scoping review guided by the Joanna Briggs Institute guidelines. The articles were searched using electronic databases including MEDLINE (PubMed), Cochrane Library, and Hinari. In addition, Google and Google scholar were searched. Studies that focused on the application of digital health technologies on COVID-19 prevention and control were included in the review. We characterized the distribution of technological applications based on geographical locations, approaches to apply digital health technologies and main findings. The study findings from the existing literature were presented using thematic content analysis. Results: A total of 2,601 potentially relevant studies were generated from the initial search and 22 studies were included in the final review. The review found that telemedicine was used most frequently, followed by electronic health records and other digital technologies such as artificial intelligence, big data, and the internet of things (IoT). Digital health technologies were used in multiple ways in response to the COVID-19 pandemic, including screening and management of patients, methods to minimize exposure, modelling of disease spread, and supporting overworked providers. Conclusion: Digital health technologies like telehealth, mHealth, electronic medical records, artificial intelligence, the internet of things, and big data/internet were used in different ways for the prevention and control of the COVID-19 pandemic in different settings using multiple approaches. For more effective deployment of digital health tools in times of pandemics, development of a guiding policy and standard on the development, deployment, and use of digital health tools in response to a pandemic is recommended.

Intelligent Cyber-Mixmechatronic Micro-System for Monitoring and Controlling the Security and Surveillance Robots

2018 ◽  
Vol 16 (14) ◽  
pp. 52-59
Author(s):  
Dorin Angelescu ◽  
Gheorghe Ion Gheorghe
Keyword(s):  
Artificial Intelligence ◽  
Motion Control ◽  
Scientific Work ◽  
The Internet ◽  
Original Solution ◽  
Control Center ◽  
Complex Project ◽  
And Control ◽  
The Internet Of Things ◽  
Surveillance Applications

Abstract As a result of the scientific concerns of the Doctoral School of Mechanical Engineering and Mechatronics at Valahia Târgovişte University in the field of robotics dedicated to security and surveillance, the scientific work "Intelligent Cyber- Mixmechatronic Micro-System for Monitoring and Controlling the Security and Surveillance Robots" is in the testing and experimentation phase, within the doctoral (industrial) thesis "Studies, research and contributions regarding the realization of a smart mecatronic robot for security and surveillance applications". The scientific work results in a highly efficient cybermixmecatronic system, unique in Romania, which will be used to control the mechatronic security and surveillance robot, respectively the propulsion and control of its displacement. The robot is controlled through Artificial Intelligence, using the Internet of Things (IoT), which is why the Intelligent Motion Control system must be optimized both in terms of response speeds and energy. At the same time, due to the varied and possibly unstable conditions of the displacement field, the system must meet stringent criteria of reliability, resilience, weather, stability and redundant solutions for on-site repair of potential failures during missions. The cybermixmecatronic system designed to move the robot must carry it safely at the mission site so that it can then return it back to the Command and Control Center. In the paper will be presented the original solution, applicable with minimum of specific modifications (according to the chassis used), to any type of robot requiring both operator-controlled or autoguid control. Thus, a complex project will be realized combining into a unitary Mechatronics, Integronics, Cyber-Mixmechatronics, Artificial Intelligence and Information Technology.

scholarly journals Approaches Based on Artificial Intelligence and the Internet of Intelligent Things to Prevent the Spread of COVID-19: Scoping Review

10.2196/19104 ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. e19104 ◽  
Author(s):  
Aya Sedky Adly ◽  
Afnan Sedky Adly ◽  
Mahmoud Sedky Adly
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Resource Allocation ◽  
Modeling And Simulation ◽  
Large Scale ◽  
Information Gathering ◽  
The Internet ◽  
Experimental Therapies ◽  
Computer Scientists ◽  
And Control

Background Artificial intelligence (AI) and the Internet of Intelligent Things (IIoT) are promising technologies to prevent the concerningly rapid spread of coronavirus disease (COVID-19) and to maximize safety during the pandemic. With the exponential increase in the number of COVID-19 patients, it is highly possible that physicians and health care workers will not be able to treat all cases. Thus, computer scientists can contribute to the fight against COVID-19 by introducing more intelligent solutions to achieve rapid control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes the disease. Objective The objectives of this review were to analyze the current literature, discuss the applicability of reported ideas for using AI to prevent and control COVID-19, and build a comprehensive view of how current systems may be useful in particular areas. This may be of great help to many health care administrators, computer scientists, and policy makers worldwide. Methods We conducted an electronic search of articles in the MEDLINE, Google Scholar, Embase, and Web of Knowledge databases to formulate a comprehensive review that summarizes different categories of the most recently reported AI-based approaches to prevent and control the spread of COVID-19. Results Our search identified the 10 most recent AI approaches that were suggested to provide the best solutions for maximizing safety and preventing the spread of COVID-19. These approaches included detection of suspected cases, large-scale screening, monitoring, interactions with experimental therapies, pneumonia screening, use of the IIoT for data and information gathering and integration, resource allocation, predictions, modeling and simulation, and robotics for medical quarantine. Conclusions We found few or almost no studies regarding the use of AI to examine COVID-19 interactions with experimental therapies, the use of AI for resource allocation to COVID-19 patients, or the use of AI and the IIoT for COVID-19 data and information gathering/integration. Moreover, the adoption of other approaches, including use of AI for COVID-19 prediction, use of AI for COVID-19 modeling and simulation, and use of AI robotics for medical quarantine, should be further emphasized by researchers because these important approaches lack sufficient numbers of studies. Therefore, we recommend that computer scientists focus on these approaches, which are still not being adequately addressed.

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