Uncontrolled garbage disposal related to urban settings can be extremely harmful to the health of individuals as well as the environment. This paper proposes the construction of an intelligent surveillance system based on the YOLOv5 object detection model and an ultra-convolutional net (U-Net), which we will call (YOLOv5-U-Net model), capable of monitoring waste management facilities in real-time through image processing and artificial intelligence. An illustration of an intelligent surveillance system is provided in the following statement. Besides identifying different categories of garbage and possible risks to public health, the system can also identify situations of unsuitable accumulation of waste. For that purpose, to ensure that local authorities will act in due time, the framework integrates several technologies, including object detection algorithms, classification networks as well as real-time warning systems. It is through the amalgamation of these technologies. Testing of the prototype has elicited an outcome; that accuracy related to waste categorization has increased, while reaction times have decreased, all discovered due to prototype examination. Implementation of this strategy does not only increase the linkage between environmental monitoring as well as protection of public health but also gives some help in promoting a conscious urban development, right through ensuring health.
The detection of faults in electronic circuits is crucial to ensure the proper performance and reliability of electronic applications that utilize these devices. This work discovers, for the first time, that a direct tester board for fault diagnosis can be used not only for the intended measurement of current and voltage but also for studying the potential development of these magnitudes in inaccessible locations, as it detects register transfer level signals through oscilloscopes with low acquisition speeds. The experimental analysis carried out combines the use of commercial software with spatial distribution tracking and the exploitation of the sizes of network links in their computer graphical representation. The proper detection of malfunctions in electronic systems is crucial for enhancing their performance and reliability. We intend to explore the troubleshooting of analog electronic systems, for which we use wide-band direct tester boards. To evaluate its performance in routine practice, we perform experimentation using two different analog circuits designed. They consist of conventional operational amplifiers and element modeling based on equivalent resistance-capacitance networks. Given the procedure followed, commercial programs were used. Special mention should be made of the conclusion matrix, which is interesting when selecting suitable diagnostic parameters. The effectiveness of direct measurement based on integrated probes in the two projects, which allowed for fault insertion, was also confirmed. The results and discussions were enriched by the summarized experimental test report. The work concludes with a reflection on the relationship between this work and the existing state of the art, as well as the new challenges posed by international researchers.