For patients with Type 1 diabetes mellitus (T1DM), accurate carbohydrate counting (CC) is essential for successful blood glucose regulation. Unfortunately, mistakes are common and may lead to an incorrect dosage of prandial insulin. In this work, we aim to demonstrate that each person has their own limits for CC errors, which can be computed using patient-specific data. To validate the proposed method, we tested it using several scenarios to investigate the effect of different CC errors on postprandial blood glucose. Virtual subjects from the T1DM Simulator were used in a clinical trial involving 450 meals over 90 days, all following the same daily meal plan but with different intervals for CC errors near, below, and above the limit computed for each patient. The results show that CC errors within personalized limits led to acceptable postprandial glycemic fluctuations. In contrast, experiments where 50% and 97.5% of the meals present a CC error outside the computed safe interval revealed a pronounced degradation of the time in range. Given these results, we consider the proposed method for obtaining personalized limits for CC errors an excellent starting point for an initial assessment of patients’ capabilities in CC and to provide appropriate ongoing education.

Many of the issues that require resolution are not easy to mitigate just from the technology perspective. The ancestral learned logic of processes, the people traditions, and many other variants define inner contexts that make the adhesion and efficient use of information technologies a delicate process. The enormous geographical dispersion of the beekeeping economic activity, the mostly amateur profile of beekeepers, and the specificity in the traditional way as the activity is managed, compromises the applicability of integrative measures based on ICTE. Efficient and integrated management of a no-professionalized economic activity depends on two basic principles: i) the existence of effective tools capable of managing that activity and its synergies with other related activities, and ii) an infrastructure (technological, procedural, legal) that supports services properly profiled for any actor in that activity. This paper describes the work-in-process sBee - Smart Beekeeping, an applied research project that sought to integrate emerging technologies on the innovative management of critical issues that beekeeping needs to overcome. Electronic devices, Internet-of-things, advanced management algorithms, and innovative visualization services were explored. The global system architecture, its supporting services, and the communication infrastructure are here described. The integration of both internet-of-things and communications services, with the common beekeeping’s management tasks, levered a proposal for improving this activity to become more effective. Furthermore, an advanced technological supporting platform was created and experimented, prepared for further developments, on mitigating emergent challenges that the digitization promotes, namely the security and traceability on food and related agriculture value-chains, as well as on the predictive and intelligent perception of current and future scenarios.