A pilot anaerobic bioreactor requires near-daily monitoring and frequent maintenance. This study aimed to upgrade a pilot bioreactor into a low-cost IoT device via ESP32 microcontrollers. The methodology was based on remote data acquisition and online monitoring of various parameters towards assessing the anaerobic digestion performance. A semi-continuous tank bioreactor with a 60 L total volume was initially inoculated mainly with livestock manure and fed daily with a mixture of glucose, gelatin, and oleic acid, supplemented with a basic anaerobic medium. Under steady-state conditions, the organic loading rate was 2 g VS L_R⁻¹ d⁻¹. Sensors for pH, temperature, REDOX potential, and ammonium concentration, along with devices measuring biogas volume and methane content, were integrated and validated against analytical methods. Biogas production was recorded accurately, enabling the early detection of production declines through ex-situ data analysis. Methane concentration variance was less than 6% compared to gas chromatography, while temperature and pH deviations were 0.15% and 1.67%, respectively. Ammonia ion measurements required frequent recalibration due to larger fluctuations. This IoT-enhanced system effectively demonstrated real-time monitoring of critical bioreactor parameters, with ESP32 enabling advanced control and monitoring capabilities.

Agricultural product drying is of great importance as it is a reliable method for fruit and vegetable preservation. Tackling the high energy consumption of the process will reduce the final product cost and mitigate greenhouse gas emissions. In this work, a passive drying method was experimentally evaluated. The method was based on the principle of the stack effect taking place in the solar chimney structure. Different types of solar chimneys in terms of dimensions and materials were evaluated for the drying of banana and potato slices. The results of the experiments showed that the drying rate was close to solar drying systems. Parameters such as height and material characteristics of drying tubes, as also weather conditions, influenced the drying rate. It was found that the banana and potato slices were dried at a satisfactory rate for almost 48 h during the summer period in Greece. From the parameters of the drying tubes that were varied, it was found that both the height and material played a major role, as did the air flow rate. With the increase in the drying tube by 1 m and with the choice of proper manufacturing material, an increase in the flow rate between 40% and 100% can be achieved. When only the color of two 3 m-high tubes changed, the flow rate varied between 4% and 15%. The proposed method has almost zero energy consumption, and it could be used as a standalone or as a part of a hybrid drying system. It can also be adjusted in existing greenhouse-type agricultural structures as a parallel operation system.

Cold stress in sheep is usually overlooked, even though the animals’ welfare and productivity are affected by low temperatures. The aim of this research was to find out if and to what extent the temperature inside a sheep barn could be maintained within the range of the thermoneutral zone during winter, primarily to increase feed conversion and to reduce GHG emissions. For this reason, an automation system was installed at a sheep barn in northern Greece, and heat losses from the building were calculated. The biogas potential of the sheep barn waste was examined in the laboratory via the BMP method. The results showed that the installation of an automation system together with a hypothetical biogas heating system could maintain the barn’s temperature in the range of a sheep’s thermoneutral zone during winter for the 94% of the scenarios examined if the total energy of the biogas was utilized, while heating energy that was instantly and continuously used succeeded in 48% of the investigated cases. The surplus of energy produced by biogas could potentially raise the water temperature that animals drink up to 2.9 °C. The absence of cold stress decreases the dry matter intake and the CH₄ produced by ruminal fermentation. Moreover, lower GHG emissions are achieved as waste is treated through anaerobic digestion, which would likely be released into the environment if left untreated.

The present study focuses on the working volume reduction of anaerobic reactors in biogas plants, which is caused by inorganic material accumulation and inadequate mixing and affects methane production and plant profitability. Precipitation phenomena lead to periodic reactor cleaning processes, which complicate the operation of the plant and increase its operating costs. For this purpose, the bioconversion model (BioModel) was utilized by modifying its conditions to accurately simulate the reduction of the working volume of a biogas plant facing precipitation problems for a study period of 150 days. The modified BioModel exhibited notable results in the prediction of methane production, with an average deviation of 1.97% from the plant’s data. After validation, based on the model results, an equation was set up to predict the optimal reactor cleaning period. Incidentally, the optimal cleaning time was calculated at 5.1 years, which is very close to the period during which the cleaning of the reactors of the studied biogas plant took place (5.5 years). The findings of this research showed that the modified BioModel, along with the developed equation, can be effectively used as a tool for the prediction of the optimal reactor cleaning period.