With the rapid advances in sensor technology, a vast and ever-growing amount of data in various domains and modalities is readily available. However, presenting raw signal data collected directly from sensors is sometimes inappropriate due to the presence of, for example, noise or distortion, among others. In order to obtain relevant and insightful metrics from sensor signals' data, further enhancement of the sensor signals acquired, such as noise reduction in one-dimensional electroencephalographic (EEG) signals or color correction in endoscopic images, and their analysis via computer-based medical systems, is needed. The processing of the data in themselves and the consequent extraction of useful information are also vital and included in the scope of this Special Issue. This SI of Sensors is aimed at highlighting advances in the development, testing, and application of data, signal, and image processing algorithms and techniques to all types of sensors and sensing methodologies. Experimental and theoretical results along with review papers, in as much detail as possible, are also considered. Some examples of the topics to be covered in this SI include the following: Ambient assisted living; Biomedical signal and image analysis; Machine learning in signal and image processing; Multimodal information processing for healthcare, monitoring, and surveillance; Real-time signal and image processing algorithms and architectures; Remote sensing processing; Sensors and smart sensors for IoT devices; Signal and image processing and understanding; Wearable sensor signal processing and its applications.