2771-1463ISSN (Online)
2771-1471ISSN (Print)
Corona virus disease(COVID-19) is a disease caused by the new corona virus called severe acute respiratory syndrome corona virus (SARS CoV-2). This disease has infected almost the entire world with a total of 47.5 million sufferers and a death total of 1.2 million people, WHO categorizes it as a global pandemic. Proven efforts to reduce the spread of COVID-19 include limiting physical interactions between humans or physical distance, maintaining the cleanliness of hands and limbs by washing with soap, and limiting outdoor activities by staying at home. Government and private agencies have required employees to report their health conditions via web pages. Real-time and accurate mobile applications can help prevent the spread of COVID-19. This research will develop a real-time monitoring and command system using mobile applications and cloud computing technology. The application will collect GPS-based location data and the user's body condition in the form of temperature and oxygen levels in the blood. User data is stored and processed in a real-time database in cloud computing which can be accessed through an application on the user's smart phone. The database also stores data on COVID-19 sufferers and where they live. Advice is given by the app when the recording of the body condition points to the early symptoms of COVID-19.
Read MoreDoi: https://doi.org/10.54216/JCHCI.020201
Vol. 2 Issue. 2 PP. 40-49, (2022)
The computerized version of human intelligence is Artificial Intelligence(AI). Artificial Intelligence systems combine large sets of data with intelligent and iterative processing algorithms in order to make predictions, based on patterns and features in the data that they analyse. With the booming technologies such as IOT and Cloud Computing, huge amounts of data are generated and collected that require cyber security protection today. There is a growing need for cyber security methods which are both robust and intelligent due to the ever-increasing complexity of cyber crimes. While data can be used to benefit business interests, it poses a number of challenges in terms of security and privacy protection. Artificial Intelligence (AI) based technologies, such as machine learning statistics, big data analysis, deep learning and so on, have been used to deal with cyber security threats. These technologies are used for intrusion detection systems, malicious software detection, and encrypted communications. In the rapidly growing field of AI driven security, scientists from multiple disciplines work together to combat cyber threats. AI models require unique cyber security defence and protection technologies. This survey provides various method, different datasets and methodologies that may be used for the proposed IA enabled cyber security technologies. This study aims to classify the AI-based cyber security solutions gathered and describe how they can help solve problems in the field of cyber security.
Read MoreDoi: https://doi.org/10.54216/JCHCI.020202
Vol. 2 Issue. 2 PP. 50-55, (2022)
There is an enormous growth of social media which fully promotes freedom of expression through its anonymity feature. Freedom of expression is a human right but hate speech towards a person or group based on race, caste, religion, ethnic or national origin, sex, disability, gender identity, etc. is an abuse of this sovereignty. It seriously promotes violence or hate crimes and creates an imbalance in society by damaging peace, credibility, and human rights, etc. To overcome this problem, the hate speech detection model is made which will classify the speech and if the speech used by user is containing hate word, it will be detected and system will sent an alert message to user about it. In order to solve various hate speech problems we use some of the machine learning algorithms such as logistic regression and random forest. If user disrupts cyber guidelines, then strict action shall be taken and user’s account will be ban forever. This help to reduce cyber crimes in effective and efficient manner.
Read MoreDoi: https://doi.org/10.54216/JCHCI.020203
Vol. 2 Issue. 2 PP. 56-59, (2022)
As technology progresses, in figuring and broadcast communications, electronic images and video are playing more important roles in today's data age. The Human Face is a key component of video and audio databases utilized by observation frameworks. Recognizing and locating human features and face highlights in a photograph or series of photographs is a difficult task in unusual scenarios, such as recordings, when acoustic conditions, illumination, subject regions, and posture can vary dramatically from edge to edge. A Human Face is an automated framework that a school uses to monitor the engagement of its employees and students. Using the Real-Time Face Recognition utility, distinct customer faces are identified and perceived with the information base to look after a company's representatives and their activities. Although the cloud offers numerous advantages, it does have one clear disadvantage: the level of protection required to access user data. The cloud poses the possibility of unauthorized access to user data. The user data was taken from the cloud application due to a security issue in the cloud. As a result, many people are concerned about their data. So, in this study, we'll use Face Recognition Technology to solve the problem. Using Artificial Intelligence Face Recognition The user is the only one who has access to the cloud. If someone else tries to access or steal data from the cloud, it will notify the user. User data may be safeguarded and only the verified user can access the Cloud utilizing real Face Recognition Technology.
Read MoreDoi: https://doi.org/10.54216/JCHCI.020204
Vol. 2 Issue. 2 PP. 60-64, (2022)
Counterfeit goods have become particularly crucial issue in the product manufacturing industry in recent years. This phenomenon has an impact on company sales and profits. This problem affects a variety of industries, including pharmaceuticals, electronics, jewellery, and cosmetics. We also recognize that in today's fast changing digital environment, smartphones have become both common and necessary. Various smartphone applications have been developed, allowing us to increase our productivity while also saving time. In recent years, several digital technologies have been introduced, such as QR codes, barcodes, OTP verification, call verification, and so on for detecting falsified products. However, due to reasons such as complicated functionality, easy cheating, and poor user experience, they were unable to implement these ideas on a large scale. A one-time QR code-based solution is used to ensure the identification of real products across the supply chain and at the consumer end, avoiding product counterfeiting. By using this system, consumers can easily differentiate between genuine and tampered or counterfeit product without any registration. The proposed system also helps the organization get data of the customers based on the region where their product is being sold. The given approach is quite scalable, fool-proof and cost effective as it uses centralized database, QR code generator and scanner.
Read MoreDoi: https://doi.org/10.54216/JCHCI.020205
Vol. 2 Issue. 2 PP. 65-71, (2022)