Abstract
The present work aims at developing a smart dental implant meant to restore the proprioceptive control of the masticatory muscle activity, in consequence of the loss of natural teeth. When periodontal afferent information is not available, the control of the occlusal forces is impaired and the capacity of regulating the masticatory force on a certain tooth or teeth is affected. The active implant being proposed detects the force exerted on teeth and proportionally generates stimuli to send that information to the brain in order to restore the neurobiological mechanisms associated to the masticatory sensory-motor function. After the description of the physiological and biomechanical aspects related to the loss of teeth and masticatory function, details are provided on the force sensing, processing and stimuli generation circuits included in the active implant being proposed. Preliminary simulation results that illustrate the implant functionality are presented.

Abstract
Natural teeth eventually fall out as one becomes older, making it more difficult chewing, speaking and get a reference plane for the body postural equilibrium. To minimize the problem, the missing teeth are eventually replaced by implants that restore the referred functions but miss the sensing of the applied force. As a consequence, the masticatory forces become erratic as the brain receives no feedback (or inaccurate) sensing information. The present work aims at developing a preliminary prototype of a smart dental implant meant to restore the proprioceptive control of the masticatory and chewing muscle activity. After the description of the physiological and biomechanical aspects related to tooth loss, details are provided on the force sensing and electrical stimulation provided by the active implant being proposed. Simulation results obtained with the development tool of the GreenPAK programmable chip being used are included.

Abstract
The aim of this chapter focuses on featuring firmed IoT architecture paradigms and advocating, knowingly in concrete use cases, the combined use of such architecture categories. It is common knowledge that the growing demand for embedded processing, interconnection, and integration facilities in everyday objects is being driven by a multitude of IoT projects. The smart cities, smart agriculture, manufacturing, and industrial automation areas are some of the most important application grounds. Equally important is the medical sector where specially framed in this publication, the personal home healthcare scenarios gain enormous relevance due to the potential of IoT technology application. It is also becoming clear that the IoT-trending efforts are compelling researchers into the concurrent combination of multiple IoT-computing architecture types or paradigms, to know: wide-range cloud-computing architectures, local-spread fog-computing architectures, and spottily scattered edge-computing architectures. This chapter focuses on identifying the major goals and benefits of each of these architectures classes; describing the relevant state of the art projects, which apply such architecture categories in home healthcare settings; and finally, pinpointing our own experience with home e-health demonstrative use case scenarios, where the benefits of using each of these architecture types become evident, and the concurrent combination of such IoT architectures inevitable. © 2021 Elsevier Inc.

Abstract
This paper presents an efficient, battery-powered, low-cost, and context-aware IoT edge computing solution tailored for monitoring a real enterprise cooking oil collecting infrastructure. The presented IoT solution allows the collecting enterprise to monitor the amount of oil deposited in specific barrels, deployed country-wide around several partner restaurants. The paper focuses on the specification, implementation, deployment and testing of ESP32/ESP8266-based end-node components deployed as an edge computing monitoring infrastructure. The achieved low-cost solution guarantees more than a year of battery life, reliable data communication, and enables automatic over-the-air end-node updates. The open-source software libraries developed for this project are shared with the community and may be applied in scenarios with similar requirements. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

Abstract
Cloud computing is omnipresent and plays an important role in today’s world of Internet of Things (IoT). Several IoT devices and their applications already run and communicate through the cloud, easing the configuration burden for their users. With the expected exponential growth on the number of connected IoT devices this centralized approach raises latency, privacy and scalability concerns. This paper proposes the use of fog computing to overcome those concerns. It presents an architecture intended to distribute the communication, computation and storage loads to small gateways, close to the edge of the network, in charge of a group of IoT devices. This approach saves battery on end devices, enables local sensor fusion and fast response to urgent situations while improving user privacy. This architecture was implemented and tested on a project to monitor the level of used cooking oil, stored in barrels, in some restaurants where low cost, battery powered end devices are periodically reporting sensor data. Results show a 93% improvement in end device battery life (by reducing their communication time) and a 75% saving on cloud storage (by processing raw data on the fog device). © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

Abstract
This paper reports on-chip rail-to-rail timing signals generation thin-film circuits for the first time. These circuits, based on a-IGZO thin-film transistors (TFTs) with a simple staggered bottom gate structure, allow row and column selection of a sensor matrix embedded in a flexible radiation sensing system. They include on-chip clock generator (ring oscillator), column selector (shift register) and row-selector (a frequency divider and a shift register). They are realised with rail-to-rail logic gates with level-shifting ability that can perform inversion and NAND logic operations. These logic gates are capable of providing full output swing between supply rails, $V_{DD}$ and $V_{SS}$ , by introducing a single additional switch for each input in bootstrapping logic gates. These circuits were characterised under normal ambient atmosphere and show an improved performance compared to the conventional logic gates with diode connected load and pseudo CMOS counterparts. By using these high-performance logic gates, a complete rail-to-rail frequency divider is presented from measurements using D-Flip Flop. In order to realize a complete compact system, an on-chip ring oscillator (output clock frequency around 1 kHz) and a shift register are also presented from simulations, where these circuits show a power consumption of 1.5 mW and 0.82 mW at a supply voltage of 8 V, respectively. While the circuit concepts described here were designed for an X-ray sensing system, they can be readily expanded to other domains where flexible on-chip timing signal generation is required, such as, smart packaging, biomedical wearable devices and RFIDs.