Biblio

Poultry farming has contributed immensely to global food security and the economy. Its produces are favourites and hugely subscribed, due to the uniqueness of their nutrients to all categories of people and the alternatives they provide to other high-cholesterol proteins. The increase in the world's population will continuously stretch for an increase in demands for poultry products. A smart way to ensure continuous production and increased yields in various farms is to adopt automated and remote management of poultries. This paper modelled and developed a collaborative system using the synergistic wireless sensor network technology and the internet of things. The system integrated resourcefully selected wireless sensors, mobile phone, other autonomous devices and the internet to remotely monitor and control environmental parameters and activities within the farm. Parameters such as temperature, humidity, water level, food valve level, ammonia gas, illumination are sensed, benchmarked against selected thresholds, and communicated wirelessly to the sink node and the internet cloud. The required control actions can also be initiated remotely by the administrator through messages or command signal. Also, the various parameters and actions can be read or documented in real-time over the web. The system was tested and evaluated to give an average of about 93.7% accuracy in parameters detection and 2s delay in real-time response. Therefore, a modelled system has been developed to provide robust and more intuitive solutions in poultry farming.

E-learning enables the transfer of skills, knowledge, and education to a large number of recipients. The E-Learning platform has the tendency to provide face-to-face learning through a learning management system (LMS) and facilitated an improvement in traditional educational methods. The LMS saves organization time, money and easy administration. LMS also saves user time to move across the learning place by providing a web-based environment. However, a few students could be willing to exploit such a system's weakness in a bid to cheat if the conventional authentication methods are employed. In this scenario user authentication and surveillance of end user is more challenging. A system with the simultaneous authentication is put forth through multifactor adaptive authentication methods. The proposed system provides an efficient, low cost and human intervention adaptive for e-learning environment authentication and monitoring system.

Rootkits detecting in the Windows operating system is an important part of information security monitoring and audit system. Methods of hided process detection were analyzed. The software is developed which implements the four methods of hidden process detection in a user mode (PID based method, the descriptor based method, system call based method, opened windows based method) to use in the monitoring and audit systems.