In the past few decades, there have been revolutionary developments in the field of smart sensing. The new era of next-generation intelligent systems is leveraging the usage of smart sensing technology to perform intelligent sensing tasks and collect useful information for different applications. Smart sensors, besides the task of collecting information from an object and converting it into an electric signal, can facilitate different diagnoses, functions, identifications, and conclusion-oriented tasks after processing the signal using advanced signal processing and artificial intelligent algorithms. The advancement of smart sensing techniques and applications is advancing rapidly and has been implemented in modern mobile devices or wearable devices. Different smart sensing systems use different types of sensors, such as temperature, pressure, infrared, proximity, light, acoustic, motion, magnetic, and vibration. This dissertation discusses secure smart sensing and applications based on the non-intrusive Photoplethysmography (PPG) sensor, which is commonly available in current wearable devices.There are different aspects of secure smart sensing systems, such as purely security-based solutions to protect smart sensing and secure applications built based on smart sensors. Our focus of this dissertation is the latter one. In this dissertation, we first study how to authenticate a user's offline/online signature with data from the PPG sensor. Conventionally, offline signatures are verified manually in the banks, and for the online signatures, dedicated electronic devices like tablets are used for verification. We propose a novel method for both offline and online signature authentication, which leverages the widely deployed PPG sensors in the wrist-worn wearable devices. The unique blood flow changes in the supplicant's hand movement are being exploited in this system to validate the signature. We design a low-cost hardware implementation to verify our proposed method. Our experiments with real-life data sets verify the feasibility and efficiency of the proposed solution. In addition, we also study a smart application of PPG sensing for weight lifting assessment. Physical activity (PA) plays an important role in a person's health. Weight lifting is one of the essential stationary exercises which helps a person maintain a fit lifestyle. It is also important for a person to be aware of the intensity of performed exercise during a workout. In our proposed work, the PPG-based system is able to classify a user's lifted weighted object into its corresponding weight label. It leverages the change in the blood volume in the wrist region that occurred due to the strain caused by the different weights being lifted in order to classify the labels. We believe the importance of PPG sensing in secure smart sensing and applications during this technology era is immense.