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With the wide popularization of Internet of Things (IoT) technology, the design and implementation of intelligent speech equipment have attracted more and more researchers’ attention. Speech recognition is one of the core technologies to control intelligent mechanical equipment. An industrial IoT sensor-based broadcast speech recognition and control system is presented to address the issue of integrating a broadcast speech recognition and control system with an IoT sensor for smart cities. In this work, a design approach for creating an intelligent voice control system for the Robot operating system (ROS) is provided. The speech recognition control program for the ROS is created using the Baidu intelligent voice software development kit, and the experiment is run on a particular robot platform. ROS makes use of communication modules to implement network connections between various system modules, mostly via topic-based asynchronous data transmission. A point-to-point network structure serves as the communication channel for the many operations that make up the ROS. The hardware component is mostly made up of the main controller’s motor driving module, a power module, a WiFi module, a Bluetooth module, a laser ranging module, etc. According to the experimental findings, the control system can identify the gathered sound signals, translate them into control instructions, and then direct the robot platform to carry out the necessary actions in accordance with the control instructions. Over 95% of speech is recognized. The control system has a high recognition rate and is simple to use, which is what most industrial controls require. It has significant implications for the advancement of control technology and may significantly increase production and life efficiency.

In synthetic aperture radar (SAR) image segmentation field, regional algorithms have shown great potential for image segmentation. The SAR images have a multiplicity of complex texture, which are difficult to be divided as a whole. Existing algorithm may cause mixed super-pixels with different labels due to speckle noise. This study presents the technique based on organization evolution (OEA) algorithm to improve ISODATA in pixels. This approach effectively filters out the useless local information and successfully introduces the effective information. To verify the accuracy of OEA-ISO data algorithm, the segmentation effect of this algorithm is tested on SAR image and compared with other techniques. The results demonstrate that the OEA-ISO data algorithm is 10.16% more accurate than the WIPFCM algorithm, 23% more accurate than the K-means algorithm, and 27.14% more accurate than the fuzzy C-means algorithm in the light-colored farmland category. It can be seen that the OEA-ISO data algorithm introduces the pixel block strategy, which successfully reduces the noise interference in the image, and the effect is more obvious when the image background is complex.

With the technological evolutionary advent, a vision-based approach presents the remote measuring approach for the analysis of vibration. The structure vibration test and model parameter identification in the detection of the structure of the bridge evaluation occupies the important position. The bridge structure to operate safely and reliably is ensured, according to the geological data of qixiashan lead-zinc mine and engineering actual situation, with the aid of international mining software Surpac. To build the 3D visualization model of the application of visualization in mine production are discussed. The results show that the final solid model of -425 stope can accurately display the spatial form of each layer of stope through rotation, amplification and movement. The proposed system is effectually able to perform cutting, volume calculation and roaming in any direction, which has certain guiding significance for mine production management. An accuracy value of 98.75%, the sensitivity of 99%, specificity of 99.64% and PPV of 99.89% are achieved using the proposed 3D modelling and visualization algorithm for vibration signal processing and management.