Intra-vehicular communication is an emerging technology explored spontaneously due to higher wireless sensor-based application demands. To meet the upcoming market demands, the current intra-vehicular communication transmission reliability and latency should be improved significantly to fit with the existing 5G and upcoming 6G communication domains. Ultra-Reliable Low-Latency Communication (URLLC) can be widely used to enhance the quality of communication and services of 5G and beyond. The 5G URLLC service is highly dependable for transmission reliability and minimizing data transmission latency. In this paper, a multiple-access scheme named Cluster-based Orthogonal Frequency Subcarrier-based Multiple Access (C-OFSMA) is proposed with 5G URLLC’s high requirement adaptation for intra-vehicular data transmission. The URLLC demanded high reliability of approximately 99.999% of the data transmission within the extremely short latency of less than 1 ms. C-OFSMA enhanced the transmission diversity, which secured more successful data transmission to fulfill these high requirements and adapt to such a network environment. In C-OFSMA, the available sensors transmit data over specific frequency channels where frequency selection is random and special sensors (audio and video) transmit data over dedicated frequency channels. The minimum number of subcarrier channels was evaluated for different arrival rates and different packet duplication conditions in order to achieve 99.999% reliability within an air-interface latency of 0.2 ms. For the fixed frequency channel condition, C-OFSMA and OFSMA were compared in terms of reliability response and other packet duplication. Moreover, the optimal number of clusters was also evaluated in the aspects of the reliability response for the C-OFSMA system.

With the increase of domestic energy consumption, an efficient energy management scheme for smart home is needed. Just as solar power can be used as a supplement to grid power in order to use smart appliances in case of grid unavailability or blackout. In this research, a load and power management system based on load priority and instant grid energy price has been proposed using Fuzzy logic algorithms. The home energy management systems (HEMS) modeled using Naive Bayes classifier shows that the loads can be shifted on or off based on grid availability, solar availability, pricing demand, urgency and loads can be changed their power source based on Interrupted, Non-interrupted, and Fixed appliances. This sort of technologies would be needed in Bangladesh whereas cost adopts grid energy price variation over time and demand. Simulation results reveal that the proposed protocol saves 47.1% ~ 48.47% of monthly electricity cost compare to the traditional scheme.