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With the current data-driven era, there is the potential to employ controllers that can store a large amount of data, which is not achievable with traditional controllers. Our goal is to propose an intelligent controller system for computer room management based on artificial intelligence that maintains data integrity, saves memory, minimizes computation, and simplifies program design. To upgrade the computer room management system’s intelligence that is not high, the management mode that is not flexible, and the distributed large-scale management of the whole school that is difficult to realize, the original system is improved to the distributed computer room management system based on artificial intelligence. By starting from the actual situation of higher vocational college computer room, combined with the characteristics of the school computer room, we designed framework model based on distributed artificial intelligence machine room management system, the system by means of network communication technology and database access technology, put forward the B/S combined with C/S structure to realize the computer room management system model, and used radio frequency identification technology to develop radio frequency card. The results show that the optimization results of the traditional computer automatic control system in the computer room vary greatly and fluctuate between 0.6 and 0.8, while the control results of the automatic control system in this paper keep stable at 0.8, which can reach the ideal state in a short time. Through the outcome, it can be said that the proposed control method can be used of higher level of automation, flexibility, and robustness which will work effectively. Therefore, the improved system integrates software, hardware, communication, and distributed system technology into one, which greatly improves the control effect of computer automatic control process, and control result of computer automatic control process is more stable and has a certain practical application value.

Nowadays over speeding is one of the most common traffic violations. Generally, over speeding is the result of restless and bad behavior of drivers. As the accident rates are increasing it is important to develop and implement a system which can automatically detect and report over speeding to the traffic control authorities as early as possible. Nearly all the roads are marked with speed limits depending upon the size of moving vehicles and heaviness of traffic, but some drivers habitually ignore this speed limit. The advancement in technology has replaced most of the manual or semi-automatic systems with an automated system. To add on to various systems in place, this research is making the use of Internet of Things to detect and report over speeding of the vehicle on which the device has been preinstalled. IoT is a technique to integrate various devices to exchange data among themselves. This research proposes the design, development and functioning of a smart device that helps in automatically detect and report to competitive authority, when so ever the subject vehicle exceeds the speed limit. The device has been developed based on the Global Positioning System (GPS) Technology using Raspberry Pi hardware and Android OS and has been practically tested on real time basis by installing it in a car.

Objectives: Al-Shifa Healthcare Information System (HIS) is developed and being used by the ministry of health in Sultanate of Oman. This case study presents the evaluation of Al-Shifa on the standard dimensions of management information system, namely, organizational dimension, management dimension and information technology dimension. Methods/Statistical Analysis: This case study employs a focus group based qualitative approach. The member of IT department at the Sultan Qaboos Hospital, Salalah, Oman formed the members of the focus group. These members are responsible for the development, support and operations of Al-Shifa, hence, provided valuable insights on which the case study has been developed. Findings: Evaluation of Al-Shifa on the standard dimension of information systems, namely, organization, management and information technology reveals that on organizational and management dimension, Al- Shifa as an HIS stands well. However, it’s chosen and present IT infrastructure is effective but not efficient. One bottleneck in its efficiency is its client-server technology which has become obsolete. Client-Server technologies are ideal for a single organization, single location information system but it certainly shouldn’t have been a choice for a country level information system, especially given the availability of web technologies and cloud computing. Similarly, a single centralized database for the entire nation would have been an ideal but its absence leads to complicated and monotonous methods of information transfer and sharing. Few healthcare units still operate as an independent unit without networking& information sharing capabilities restricting integration with other centers. Application/Improvements: The focus group included staff of IT department; however, the views of end users are not incorporated. A separate study is needed in order to collect end user’s perspective of Al-Shifa.

Automatic vehicle monitoring has turned out to be a very crucial scenario in the current years. It may develop into possibility by executing the following technologies. This project targets to propose a system, which detects speeding vehicles over a specific speed limit and immediately report to concerned authorities. At present, road accidents rates have raised so, there is a necessity for developing a system that detects an over speeding vehicle. The implementation of present Smart Vehicle Overspeeding Detector using Internet of Things determines all the road traffic information automatically with intelligence. The smart vehicles are suitable with overspeeding detector that has capability for recording, storing and information sharing about the vehicle's speed. The system contains GPS module, Radar, Google maps and IoT module. The safe regions are identified automatically using GPS and IoT technologies. Electronic tracking device runs in 12 V lithium batteries with network of GPS sensing and IoT implementation. The battery life of this device is range from 5–10 hours. A smart vehicle overspeeding sensor is employed and is combined with IoT in order to decrease the vehicle's speed at particular places like accident prone zones. If this smart sensor technology is used the safety parameters, then avoidance of accidents may be attained. The system sends the data wirelessly. If the overspeeding vehicle is detected, then the sensor alerts by sounding an alarm. The purpose of the proposed sensor is to decrease high death rates because of accidents in Middle East countries and in Oman.

Healthcare industry has perpetually been on the forefront in the adoption and utilization of information and communication technologies (ICT) for the efficient healthcare administration and treatment. Recent developments in ICT and the emergence of Internet of Things (IoT) have opened up new avenues for research and exploration in the all fields including medical and healthcare industry. Hospitals have started using the cell instruments for communication intent and for this intent internet of things (IoT) has been used and fused with wi-fi sensor node reminiscent of RFID, NFC tag and small sensor nodes. The usage of a cellular agent in healthcare procedure underneath wi-fi community environment gives a chance to explore improved services for patients and staffs reminiscent of medical professionals and nurses given that of its mobility. In this paper novel method to utilize it IoT within the field of scientific and crafty wellness care are presented. The majority of the survey exist about the different healthcare approaches used in the IoT, similar to, wireless well-being monitoring, U-healthcare, E-healthcare, Age-friendly healthcare techniques. This paper describes and proposes a complete monitoring existence cycle and effective healthcare monitoring system designed by using the IoT and RFID tags. The experimental results in this paper show the robust output against various medical emergencies. In this system to get the veracious evaluation results, supervising and weighing the health status of patient and to increase the power of IoT, the combination of microcontroller with sensors is presented.

Background/Objectives: Security is gaining its importance in today’s highly connected world. In this paper we study the application of Bayesian classifiers to improve Intrusion Detection. Methods/Statistical analysis: We compared three Bayesian classifiers that are/ can be used for Intrusion detection viz., Naive Bayes, Naive Bayes Updateable and BayesNet classifiers. These classifiers are tested using a data mining tool called WEKA. The dataset used for the course of our work (to perform comparative/ experimental evaluation) is NSL-KDD dataset. Findings: We performed the experimental evaluation of above mentioned algorithms using NSL KDD dataset. The results proved BayesNet as the better classifier; however, it still requires some improvements. BayesNet had a True Positive Rate of around 95% and False Positives were as low as 4.87% whereas both Naive Bayes and its updateable version resulted in True Positive Rate of around 80% and False Positive rate of 19.26% which is not good when compared to BayesNet. Similarly, BayesNet had lesser error rates than it counterparts. The evaluation of BayesNet resulted in the Mean Absolute Error of around 5% and Root Mean Squared Error of around 21% while in the case of Naive Bayes and Naive Bayes Updateable Mean Absolute Error was around 4times than that of BayesNet and Root Mean Squared Error was twice of the BayesNet’s. Further results and analysis are provided in the sections 7 and 8 respectively. Application/Improvements: The studied classifiers need further improvements e.g., model building time for BayesNet classifier and classification rate for the other two classifiers.