Individuals with diabetes mellitus type 1 (DM1) tend to check their blood sugar levels multiple times daily and utilize this information to predict their future glycemic levels. Based on these predictions, patients decide on the best approach to regulate their glucose levels with considerations such as insulin dosage and other related factors. Nevertheless, modern developments in Internet of Things (IoT) technology and innovative biomedical sensors have enabled the constant gathering of glucose level data using continuous glucose monitoring (CGM) in addition to other biomedical signals. With the use of machine learning (ML) algorithms, glycemic level patterns can be modeled, enabling accurate forecasting of this variable. Constrained devices have limited computational power, making it challenging to run complex machine learning algorithms directly on these devices. However, by leveraging edge computing, using lightweight machine learning algorithms, and performing preprocessing and feature extraction, it is possible to run machine learning algorithms on constrained devices despite these limitations. In this paper we test the burdens of some constrained IoT devices, probing that it is feasible to locally predict glycemia using a smartphone, up to 45 min in advance and with acceptable accuracy using random forest.

In this work a new design concept in the field of microwave heating assisted chemical reactors is proposed focusing on two main innovations. The first one consists in combining the resonant cavity and the vessel in the same volume, improving the durability of the system by using a metallic material for the vessel. The second consists of integrating antennas as applicator ports for energy transmission from the magnetron into the cavity, instead of waveguides, allowing greater design flexibility in terms of cavity and system dimensions. In this work, a microwave reactor with four electromagnetic energy emitting antennas is optimized. This innovation is evaluated by means of a simulation model that solves the finite element method (FEM) using the commercial software COMSOL Multiphysics coupling radio frequency and heat transfer physics. Within this work, simulations have demonstrated the microwave heating process in the configured chemical reactor where the implementation of standard waveguides would not be possible due to the incompatible size required in the selected diameter dimension for 106 litres. Therefore, the results achieved lay the foundation for the construction of a microwave reactor intended to drive the industrial process of chemical recycling of polymers on a large industrial scale.