2篇
您的检索式：作者名="Sultan Alamri"
|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Multi-Floor Indoor Trajectory Reconstruction Using Mobile Devices显示文摘An indoor trajectory is the path of an object moving through corridors and stairs inside a building.There are various types of technologies that can be used to reconstruct the path of a moving object and detect its position.GPS has been used for reconstruction in outdoor environments,but for indoor environments,mobile devices with embedded sensors are used.An accelerometer sensor and a magnetometer sensor are used to detect human movement and reconstruct the trajectory on a single floor.In an indoor environment,there are many activities that will create the trajectory similar to an outdoor environment,such as passing along the corridor,going from one room to another,and other activities.We need to analyse trajectories to obtain the movement patterns,understand themost frequently visited places or paths used aswell as the least frequented ones.Furthermore,we can utilize movement patterns to obtain a better building design and layout.The latest studies focus on reconstructing the trajectory on a single floor.However,actual indoor environments are comprised of multi-floors and multibuildings.The purpose of this paper is to reconstruct a trajectory in an indoor multi-floor environment.We have conducted extensive experiments to evaluate the performance of our proposed algorithms in a campus building.The result of our experiment shows that the height of the building can be detected using a barometer sensor that gives an atmospheric pressure reading which is then transformed by setting the range value according to the number of floors,enabling the sensors to detect activity in a multi-floor building.The readings obtained from the magnetometer sensor can be used to reconstruct the trajectory similar to the real path based on the direction and degree of direction.The system accuracy in recognizing steps in a multi-floor building is about 84%. | Sultan Alamri Kartini Nurfalah Kiki Adhinugraha | 2021 | Computer Modeling in Engineering & Sciences2021，，9： | 0 |
| 2 | Blockchain-Based Decentralized Authentication Model for IoT-Based E-Learning and Educational Environments显示文摘In recent times,technology has advanced significantly and is currently being integrated into educational environments to facilitate distance learning and interaction between learners.Integrating the Internet of Things(IoT)into education can facilitate the teaching and learning process and expand the context in which students learn.Nevertheless,learning data is very sensitive and must be protected when transmitted over the network or stored in data centers.Moreover,the identity and the authenticity of interacting students,instructors,and staff need to be verified to mitigate the impact of attacks.However,most of the current security and authentication schemes are centralized,relying on trusted third-party cloud servers,to facilitate continuous secure communication.In addition,most of these schemes are resourceintensive;thus,security and efficiency issues arise when heterogeneous and resource-limited IoT devices are being used.In this paper,we propose a blockchain-based architecture that accurately identifies and authenticates learners and their IoT devices in a decentralized manner and prevents the unauthorized modification of stored learning records in a distributed university network.It allows students and instructors to easily migrate to and join multiple universities within the network using their identity without the need for user re-authentication.The proposed architecture was tested using a simulation tool,and measured to evaluate its performance.The simulation results demonstrate the ability of the proposed architecture to significantly increase the throughput of learning transactions(40%),reduce the communication overhead and response time(26%),improve authentication efficiency(27%),and reduce the IoT power consumption(35%)compared to the centralized authentication mechanisms.In addition,the security analysis proves the effectiveness of the proposed architecture in resisting various attacks and ensuring the security requirements of learning data in the university network. | Osama A.Khashan Sultan Alamri Waleed Alomoush Mutasem K.Alsmadi Samer Atawneh Usama Mir | 2023 | Computers, Materials & Continua2023，，5： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员