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The artificial bee colony (ABC) algorithm is one of the classical bioinspired swarm-based intelligence algorithms that has strong search ability, because of its special search mechanism, but its development ability is slightly insufficient and its convergence speed is slow. In view of its weak development ability and slow convergence speed, this paper proposes the QABC algorithm in which a new search equation is based on the idea of quasi-affine transformation, which greatly improves the cooperative ability between particles and enhances its exploitability. During the process of location updating, the convergence speed is accelerated by updating multiple dimensions instead of one dimension. Finally, in the overall search framework, a collaborative search matrix is introduced to update the position of particles. The collaborative search matrix is transformed from the lower triangular matrix, which not only ensures the randomness of the search, but also ensures its balance and integrity. To evaluate the performance of the QABC algorithm, CEC2013 test set and CEC2014 test set are used in the experiment. After comparing with the conventional ABC algorithm and some famous ABC variants, QABC algorithm is proved to be superior in efficiency, development ability, and robustness.

The WSN uses wireless communication to realize its information transmission. WSN is a network data system composed of a large number of wireless data collectors with sensing functions. In the WSN-based sensing function structure, the size should be small, more power saving, low price, and can achieve design goals. This study first assumes that WSN uses routing algorithm assumptions in the protocol, and starts from the node position and direction information, and considers the dynamic evolution of the network. Each public node has random mobility, and the WSN node can help determine the location information of the public node, and then use the node location information to have effective routing performance and effective. However, the experimental results also strongly support the energy saving ability of this research. In the overall system energy saving and power consumption reduction, the actual electric energy hazard is greatly reduced, so in the spirit of ISD strategies, if the WSN system is installed in a high-risk and explosive atmosphere, it can significantly improve the safety level.

In recent years, evolutionary algorithms based on swarm intelligence have drawn much attention from researchers. This kind of artificial intelligent algorithms can be utilized for various applications, including the ones of big data information processing in nowadays modern world with heterogeneous sensor and IoT systems. Differential evolution (DE) algorithm is one of the important algorithms in the field of optimization because of its powerful and simple characteristics. The DE has excellent development performance and can approach global optimal solution quickly. At the same time, it is also easy to get into local optimal, so it could converge prematurely. In the view of these shortcomings, this article focuses on the improvement of the algorithm of DE and proposes an adaptive dimension differential evolution (ADDE) algorithm that can adapt to dimension updating properly and balance the search and the development better. In addition, this article uses the elitism to improve the location update strategy to improve the efficiency and accuracy of the search. In order to verify the performance of the new ADDE, this study carried out experiments with other famous algorithms on the CEC2014 test suite. The comparison results show that the ADDE is more competitive.

This research mainly uses the Wi-Fi module (ESP8266) microcontroller to implement the IoT-based smart home system. In this study of smart home system is able to power the circuit by the photovoltaic cell itself and then wirelessly switch to the required load. As technology is expanding every day, mobile, robotics, machines learning are advancing their technology then why our house is an exception. Today’s house moving slowly based on common/human input controlling to smart/IoT-enabled devices to be controlled remotely. Currently, use the existing smart home system technology that is limited to this device only. Because of this, IoT devices are now being applied in various fields, but unfortunately, low cost and simple IoT applications are still insufficient in smart home. However, this study is concerned with the Node MCU (ESP8266) microcontroller used to control the power switches remotely. The users can control witches using web application after authenticating based on low cost and simple IoT application systems; this study has important contributions to the development of smart homes with high price–performance ratio in future.

In terms of fire outbreak, the nature of some big industries and thermal plants seems extremely volatile. The existence of oxygen and fuel cannot be taken out in thermal power plant, and many actions may be originated from heat source. Many researchers have developed more interest in the research field of fire detection in some big industries and thermal plants, especially those who use hydrocarbon-based product as fuel. The fire that normally occurs at these places is normally class B type of fire, and carbon dioxide is used to put them off. This paper proposes a design of an automated fire alarm system which utilizes already existing technologies such as the wireless sensor network technology and carbon capture and storage system to help alleviate the problem of global warming and reduce the cost incurred in existing ineffective fire alarm system. During combustion process in the thermal plant, the carbon dioxide emitted is captured and stored to be used to put off or suppressing fire after early detection by the wireless sensor network with sensors such as optical flame detectors, heat detector, and hydrogen detector. The simulations done on the final designs proved that this system is feasible and can be successfully deployed on a larger scale.