# Recent Trends in AI-Based Intelligent Sensing
## 4 Practical Applications of Intelligent Sensing
### Applications of Intelligent Sensing
The use of intelligent sensing with edge computing and cloud services are also encouraging several corporations and startups to work in the area. UNet++ [155] was proposed for medical image segmentation and has been successfully implemented on computed tomography scan, microscopy, and RGB video data. The UNet++ architecture is the new version in the series of U-Net and wide U-Net architecture. It has been observed that with deep supervision, UNet++ has demonstrated better performance than its predecessors. The common issue in implementing the intelligence for disease detection using sensors is that the raw data need to be segmented and labeled for further analysis. In case urgent or fast results are required, a manual method is preferred as in incorporating intelligence to algorithms, training needs to be done by feeding information in significant amounts. If the system is not trained, the accuracy of such a model will be degraded, which will affect the end result, i.e., successful prediction of true positive cases. The nucleic acid test is a method used to identify the cases related to the diagnosis of Gonococcal and other Neisseria infections, HIV RNA, Severe Acute Respiratory Syndrome (SARS), coronaviruses, etc. A recent study shows that it is also being considered for the diagnosis of COVID-19 patients. This test helps detect specific nucleic acid sequences and organisms in blood, tissue, urine, or stool. The work in [156] proposed nucleic acid amplification tests (NAATs) using stacked denoising autoencoders (SDAE) for feature extraction. It is also observed that DeepGene, a cancer type classifier, can be essential [157]. In another work [158], [PERSON] et al. have implemented CNN to recognize the behavior of pulmonary nodules and also to extract features for machine-generated endoscopy images in low light. As observed, artificial intelligence algorithms are increasingly implemented in pathology devices with assistive methods to achieve high accuracy results. In the monitoring of pandemic and epidemic also, such intelligent sensing plays a vital role. Thermography devices can be easily found in public places, especially in the case of mass spreading diseases. Thermal scanner is a commonly known device to identify the fever by interpreting the data (heat map) in human-readable forms. Figure 7 is a case study on the importance of intelligent sensing in epidemic and pandemic. To detect the symptoms related to the infection, multiple tests are proposed, and in most of the cases, a combination of such tests needs to be performed. WHO suggests swab test, which requires the sample collection from nose and throat. On the other hand, in CT scan images are used, and test data need to be further analyzed in thermography to sort out potential patients based on the heat analysis. The tissues collected by biopsy and bronchoscopy are examined to understand the symptoms. Urine and stool tests have also shown the presence of infection in patients. In the case of COVID-19, urine samples are not adequate, and stool analysis has helped detect the presence of infection, similar to SARS and MERS. Blood tests will help analyze cell culture, and multiple serology assays will help identify the virus growth and immune system status. Tests such as RDT, ELISA, and Neutralization assay indicate the presence of antibodies with the possibility of protection against infection. Data from multiple test sources shown in Figure 8 are helpful for training and testing algorithms. Deep learning and artificial intelligence algorithms trained with such data will further help in symptom identification. 5. Smart Assistive technology--In [159], a navigation system for visually impaired people is developed. This project focuses on how place cells, grid cells, and track integration along with AI can be helpful. Artificial intelligence with grid cells uses deep Q learning with an RNN-based ANN architecture. In [160], cash recognition for blind people is designed to allow those people to identify the notes correctly.