The Internet of Electric Vehicles (IoEV) comprises of digital technologies and Electric vehicles (EVs) to provide green communication, exchange of data and remote monitoring. IoEV is subjected to the critical challenge of scheduling and routing for optimizing EVs movement based on constraints and opportunities to make the usage of energy efficient. This paper proposed a novel Associative Rule mining integrated with Hidden Markov Model Probabilistic Sugeno Fuzzy (AiHMM - PSF) for the routing and scheduling with minimal operating cost and travel delays with improved charging energy efficiency. The proposed AiPSF model utilizes available resources, to generate associative rule for effective routing with the optimal path selection. Through computed routes Hidden Markov Model with Probabilistic computation is employed for the estimation of optimization path in the IoEV for the energy harvesting. The proposed AiHMM - PSF uses the Adaptive neuro-fuzzy inference system (ANFIS) for the operation optimization to perform routing. Experimental results demonstrated that the proposed AiHMM - PSF model achieves an average charging cost of $13.2 per EV, which is 16.5% lower than the traditional fuzzy logic model ($15.8 per EV). In addition, energy consumption is decreased for proposed AiHMM - PSF from 53.6 kWh to 47.1 kWh, which is ~ 12.1 % of energy efficiency. Through implementation of associative rule-based routing in proposed AiHMM – PSF reduces the average travel delay to only 6.4 minutes, compared to 9.1 minutes that is predicted by the existing model by ~ 29.7%. The charging station energy utilization also achieves 82.7% with the proposed AiHMM - PSF, which outperforms the traditional model’s utilization of 75.4%. The results stated that the proposed AiHMM - PSF effectively optimizes the selection of charging stations and effective green communication scheduling, which increases the total efficiency with significant energy harvesting in IoEV networks.

We propose EDGE (An Easy Design Tool of Game Event for Rapid Game Development), with it game designers can make game events and effects without detailed programming skill. In the typical game design phase, the programming of game events is time consuming, non-productive, and burden to programmers; moreover, it is very difficult task for non-programmers. In this paper, we propose EDGE based game design process which clearly guarantees independence of game planning/design phase from the game programming phase. In the game design phase, game designer make events/effects without programming details. After verification of design process by EDGE preview, we can proceed to the game implementation phase, where we can use EDGE generated game source codes. We design and implement EDGE on OpenGL platform, applied EDGE on the development of two major genres of game contents, and the experimental results show that we can increase the productivity and the design maintenance.