Enhanced Water Quality Control Based on Predictive Optimization for Smart Fish Farming

The requirement for high-quality seafood is a global challenge in today’s world due to climate change and natural resource limitations.Internet of Things(IoT)based Modern fish farming systems can significantly optimize seafood production by minimizing resource utilization and improving healthy fish production.This objective requires intensive monitoring,prediction,and control by optimizing leading factors that impact fish growth,including temperature,the potential of hydrogen(pH),water level,and feeding rate.This paper proposes the IoT based predictive optimization approach for efficient control and energy utilization in smart fish farming.The proposed fish farm control mechanism has a predictive optimization to deal with water quality control and efficient energy consumption problems.Fish farm indoor and outdoor values are applied to predict the water quality parameters,whereas a novel objective function is proposed to achieve an optimal fish growth environment based on predicted parameters.Fuzzy logic control is utilized to calculate control parameters for IoT actuators based on predictive optimal water quality parameters by minimizing energy consumption.To evaluate the efficiency of the proposed system,the overall approach has been deployed to the fish tank as a case study,and a number of experiments have been carried out.The results show that the predictive optimization module allowed the water quality parameters to be maintained at the optimal level with nearly 30%of energy efficiency at the maximum actuator control rate compared with other control levels.

Towards a Dynamic Virtual IoT Network Based on User Requirements

The data being generated by the Internet of Things needs to be stored,monitored,and analyzed for maximum IoT resource utilization.Software Defined Networking has been extensively utilized to address issues such as heterogeneity and scalability.However,for small-scale IoT application,sometimes it is considered an inefficient approach.This paper proposes an alternate lightweight mechanism to the design and implementation of a dynamic virtual network based on user requirements.The key idea is to provide users a virtual interface that enables them to reconfigure the communication flow between the sensors and actuators at runtime.The throughput of the communication flow depends on the data traffic load and optimal routing.Users can reconfigure the communication flow,and virtual agents find the optimal route to handle the traffic load.The virtual network provides a user-friendly interface to allow physical devices to be mapped with the corresponding virtual agents.The proposed network is applicable for all systems that lie in the Internet of Things domain.Results conclude that the proposed network is efficient,reliable,and responsive to network reconfiguration at runtime.

State of the Art Vibration Analysis of Electrical Rotating Machines

Electrical machines are precarious mechanisms in manufacturing practices. A motor failure may yield an unexpected interruption at the industrial plant, with consequences in costs, product quality, and security. To govern the conditions of each part of motor, various testing and monitoring methods have been developed. In this paper, a review on effective fault indicators and vibration based condition monitoring approaches of rotating electrical machines has been accomplished. The determination of the review is to progress the understanding of vibration based analysis, and its use in the Machine Health Monitoring. A variety of analysis was identified to highlight the concept of predictive maintenance in industries. The techniques of vibration analysis were investigated to detect both healthy and fault related signals of rotating machineries.

Impact of Accelerated Ultraviolet Weathering on Polymeric Composite Insulators Under High Voltage DC Stress

This study investigates the weatherability of room temperature vulcanized(RTV)silicone rubber(SiR)and epoxybased material specimens with a composition of different nano and micro fillers against the collegial effects of high voltage DC,UV and temperature stresses.Bulk power transmission over long distances via HVDC is considered an economic option these days,so to ensure the system reliability,it is also critical to investigate these insulators under DC stress along with other environmental stresses(especially UV and temperature).For experimentation,composite samples i.e.neat epoxy(NE),epoxy with 15%micro SiO_(2)(EMS),epoxy with 5%nano SiO_(2)(ENS),neat SiR(NS),SiR with 15%micro SiO_(2)(SMS)and SiR with 5%nano SiO_(2)(SNS)are fabricated and subjected to accelerated aging in a weather chamber for 3,360 hours.Results reveal that SMS and SNS offer better hydrophobic behavior followed by EMS.However noticeable surface discoloration in the form of whitish shade with minor blackish spots is found in the case of SMS,while remaining samples also showed considerable color fading.Scanning electron microscopy(SEM)and Fourier Transform Infrared Spectroscopy(FTIR)results showed that SNS and SMS presented quite excellent resistance to the exposure of fillers.Hardness and weight of all specimens are evaluated throughout the experiment and particularly for the water immersion test.Moreover,leakage current analysis indicated that SNS and SMS revealed high leakage current suppression compare to other samples.Findings indicate that SNS and SMS showed enhanced resistance against UV weathering under high voltage direct current stress.