The demand for multimedia data services has grown up rapidly over the years. Fifth generation (5G) wireless communication which has been deployed in a lot of countries will not be able to meet up with users demand based on the estimated mobile traffic volume of users in the next few years. Therefore, the sixth generation (6G) communication has been proposed to address the constraints/limitations of 5G communication. 6G systems will operate in the millimeter wave (mmWave) and terahertz region which has larger bandwidth and offers higher data rate than 5G systems. 6G has a lot of opportunities like high-definition imaging, frequency spectroscopy, accurate localization and sensing, which is the main focus of this work. There are a lot of opportunities for sensing at higher frequencies because of fine resolution in all physical dimensions (range, Doppler and angle). Moreover, localization and sensing in 6G is made possible by the key enablers technologies which are: the use of new radio band for communication, intelligent beam-space incorporation of intelligent surfaces, artificial intelligence and machine learning methods. In the new proposed 6G system, it is necessary for localization, sensing and communication to coexist, sharing the same time-frequency-spatial resources. In other to enable sharing, cooperation, coexistence and co-design, various mechanisms and approaches are needed in 6G communication systems.

A wireless sensor network (WSN) comprises of sensor nodes (SNs) deployed for various purposes such as target tracking, target monitoring and localization. The rising need for individuals to access localization-based services has given rise to the emergence of localization techniques in WSN s. Localization means acquiring some information about objects of interest from multiple points in a particular location or area. Applications of localization can be found in autonomous vehicles, Internet of Things etc. This study presents an analysis and review of localization techniques in WSNs. We identified the merits and the demerits of different localization techniques. Future research on localization in WSN should focus on; developing a secure 3-D localization technique for underwater ecosystems and development of an efficient localization technique that can adapt for different environments, both indoor and outdoor.

The traditional power grid is considered no longer viable because it is old, overstretched, unreliable hence the reason for the transformation into the smart grid (SG). The Future SG will have monitoring, automation and communication capabilities which is the main focus of this paper. The SG can also provide two-way communication, real-time pricing and demand-side management. It will have self-healing capability in the case of any fault in the system, unlike the conventional power grid. Furthermore, the SG will have renewable energy resources (RER), advanced metering infrastructure(AMI), supervisory control and data acquisition (SCADA) and plug-in electric vehicles (PEVs) as the essential blocks of SG. The reliability of the SG can be guaranteed by intelligent monitoring and control system with robust information and communication technology. This paper provides a survey of the SG system, a basic overview of the SG, a summary of the various types of communication technologies that can be used in the SG, the requirements for smart grid communication in other to have an effective and efficient communication system and finally, the future trends of SG communication.

This paper presents an optimal PID controller for speed control of DC motor using Smell Agent Optimization (SAO) Algorithm. DC Motor is an energy converter which transforms electrical energy into mechanical energy used in several industrial applications. A SAO based PID is proposed for optimal tuning of the parameters of the controller to improve speed control of the motor. The SAO uses the phenomenon of smell perception and the intuitive trailing behavior of an agent to identify the source of smell. The integral of time multiplied absolute error (ITAE) is taken as the objective function for obtaining the parameters of the PID controller. It has been observed SAO-PID controller outperforms the GA based PID controller with less settling time, rise time and overshoot. Keywords— DC motor, PID controller, rising time, settling time, smell agent optimization algorithm

Wireless sensor nodes (SNs) are deployed for wide range of applications like military surveillance, disaster warning, environmental monitoring etc. The performance of SNs degrades with time due to finite amount of energy, which affect the network lifetime and the quality of service. To improve the network lifetime, the on-demand Wireless Rechargeable Sensor Network (WRSN) was proposed. In WRSN, the SNs are charge wirelessly using mobile chargers (MCs). The main problem with the on-demand WRSN is the design of optimal charge scheduling to reduce charge latency of the SNs. The paper has presented the review on the different on-demand wireless rechargeable techniques in the literature. Recommendations for the design of an efficient on-demand charging technique to improve network lifetime and quality of service for large scale WRSN is made for future research.

Wireless rechargeable sensor networks (WRSNs) addressed the energy bottle-neck inherent in Wireless sensor Networks (WSN) by utilizing mobile chargers to travel and replenish the energy of nodes. Most WRSNs schemes operate by allowing simultaneous data gathering with energy recharging. This increases the storage and processing power requirements of the nodes and their overall design cost. A non-concurrent data gathering and energy replenishment in WRSNs named Spatio-Temporal Non-Concurrent Data gathering and energy Recharging (ST-NCDR) is hereby proposed to enable realistic deployment of WRSNs using low-cost sensors that can easily be implemented. Simulation results indicate that the developed scheme has a lower energy consumption of the mobile chargers (MCs) and also a higher average residual energy of nodes than a scheme that executes the two tasks simultaneously.