In the last decade, the Internet of Things (IoT) has become a new technology that aims to facilitate life and help people in all aspects of their lives. This technology is used for smart homes, smart grid stations, smart agriculture, health systems, transport services, smart cities, etc. The number of sensors and IoT devices along with applications is used for monitoring the health condition of patients. These devices will monitor the movement of targeted patients at home or out of their homes. Based on their behavior and movement, the treatment will be provided to Alzheimer’s patients. The data will be collected from multiple sensors installed at patient’s homes and smartwatches for checking their blood pressure level and temperature, which is too important in the current Corona Virus Disease (COVID-19) pandemic for these types of patients. On the other hand, due to the diminishing mobility of people around the world, increasing environmental pollution and stress which is caused by modern machine life and various brain and neurological diseases including Alzheimer’s, Parkinson, etc. are widespread among people all over the world. The different types of communication protocols such as Message Queue Telemetry Transport (MQTT) and WebSocket (with authentication and autoclosing of connection) for sensors and the smartwatch have been used. The secure backend admin panel is used for tracing the location of doctors, patients, and ambulance. These protocols are implemented with security to protect the privacy of patients also.
Several research works are attempted to predict students academic performance and assess  the  evaluating students knowledge  or  detecting  students’  weakness and probability of failure in final semester examinations. However, several factors affect the performance of students in different countries or even in different states of one country. Therefore, understanding these factors and analyzing the effects of each one of those factors in each country, is necessary for improving instructors’ decisions in selecting  the best teaching method for helping weak students or  increasing performance  of  other  students. This study is motivated  to  study  the  students’ academic performance in high  school  and  bachelor  degree  studies  in  Iran and comparing these analysis results with the similar study’s results in India.
Crime is a bone of contention that can create a societal disturbance. Crime forecasting using time series is an efficient statistical tool for predicting rates of crime in many countries around the world. Crime data can be useful to determine the efficacy of crime prevention steps and the safety of cities and societies. However, it is a difficult task to predict the crime accurately because the number of crimes is increasing day by day. The objective of this study is to apply time series to predict the crime rate to facilitate practical crime prevention solutions. Machine learning can play an important role to better understand and analyze the future trend of violations. Different time-series forecasting models have been used to predict the crime. These forecasting models are trained to predict future violent crimes. The proposed approach outperforms other forecasting techniques for daily and monthly forecast.
The energy of sensor nodes in wireless sensor networks is limited, which is one of the most important challenges due to the lack of a fixed power supply. Because data transmission consumes the most energy of nodes, a node that transmits more packets runs out of energy faster than the others. When the energy of a node comes to the end of a network, the process of network operation may be disrupted. In this case, critical information in the network with the desired quality may not reach the hole and eventually the base stations. Therefore, considering the dynamic topology and distributed nature of wireless sensor networks, designing energy-efficient routing protocols is the main challenge. In this paper, an energy-aware routing protocol based on a multiobjective particle swarm optimization algorithm is presented. In the proposed particle swarm optimization algorithm method, the proportionality function for selecting the optimal threaded node is set based on the goals related to service quality including residual energy, link quality, end-to-end delay, and delivery rate. The simulation results show that the proposed method consumes less energy and has a longer lifespan compared with the state-of-the-art methods due to balancing the goals related to service quality criteria.
As the SQL injection attack is still at the top of the list at Open Web Application Security Project (OWASP) for more than one decade, this type of attack created too many types of issues for a web application, sensors, or any similar type of applications, such as leakage of user private data and organization intellectual property, or may cause Distributed Denial of Service (DDoS) attacks. This paper focused on the poor coding or invalidated input field which is a big cause of services unavailability for web applications. Secondly, it focused on the selection of program created issues for the WebSocket connections between sensors and the webserver. The number of users is growing to use web applications and mobile apps. These web applications or mobile apps are used for different purposes such as tracking vehicles, banking services, online stores for shopping, taxi booking, logistics, education, monitoring user activities, collecting data, or sending any instructions to sensors, and social websites. Web applications are easy to develop with less time and at a low cost. Due to that, business community or individual service provider’s first choice is to have a website and mobile app. So everyone is trying to provide 24/7 services to its users without any downtime. But there are some critical issues of web application design and development. These problems are leading to too many security loopholes for web servers, web applications, and its user’s privacy. Because of poor coding and validation of input fields, these web applications are vulnerable to SQL Injection and other security problems. Instead of using the latest third-party frameworks, language for website development, and version database server, another factor to disturb the services of a web server may be the socket programming for sensors at the production level. These sensors are installed in vehicles to track or use them for booking mobile apps.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.