Power loss is one <span lang="EN-US">of the important pointers used to measure the performance of distributions networks. Many optimization algorithms have been proposed to solve various optimal power flow problems in Electrical Engineering. In this paper, a novel technique, artificial algae algorithm is developed to robustly detect the optimal location and size of distributed generation (DG) units for minimization of total power losses without violating the equality and inequality constraints. The main objective of optimal power flow (OPF) is to maximize or minimize the objective function using various constraint so that steady-state operation point is achieved. The concept of optimal power flow in power system helps to minimize real power loss. In the proposed approach, various control variables like generator bus, voltage magnitudes, and transformer tap settings are considered. The proposed algorithm is simulated in MATLAB and effectiveness is carried on IEEE 33 bus radial distribution system and satisfactory results are achieved when compared with other optimization techniques. A notable improvement in reduction of active power losses with 3 DG operating at different power factors are 65.5%, 42.4%, and 77.8% respectively, were achieved in comparison to the system without DGs and as compared with other research papers.</span>

Smart cities have benefited greatly from the quick development of information technology, such as cloud computing, sensors, and the IoT. Smart cities improve living services and analyze massive amounts of data, which increases privacy and security concerns. But managing security and privacy issues is crucial for a smart city that encourages businesses to adopt new computing paradigms. In recent years, there has been a proliferation of literature on security and privacy, covering topics like end-to-end security, reliable data acquisition, transmission, and processing, legal service provisioning, and privacy of personal data, as well as the application of bio inspired computing techniques to system design and operation. Effective computing systems have been developed by utilizing bio-inspired computing approaches for intelligent decision support. The indicator-based threat detection system with BAAA algorithm is the quickest and most efficient way to scope an environment after observation, and its usefulness is greatly influenced by the adversary rate of change.