Harvest Stage Recognition and Potential Fruit Damage Indicator for Berries Based on Hidden Markov Models and the Viterbi Algorithm

This article proposes a monitoring system that allows to track transitions between different stages in the berry harvesting process (berry picking, waiting for transport, transport and arrival at the packing site) solely using information from temperature and vibration sensors located in the basket. The monitoring system assumes a characterization of the process based on hidden Markov models and uses the Viterbi algorithm to perform inferences and estimate the most likely state trajectory. The obtained state trajectory estimate is then used to compute a potential damage indicator in real time. The proposed methodology does not require information about the weight of the basket to identify each of the different stages, which makes it effective and more efficient than other alternatives available in the industry

Calibration of Sensor Network for Outdoor Measurement of PM2.5 on High Wood-Heating Smoke in Temuco City

2023 Descuento MDPIIn order to ascertain the spatial and temporal changes in the air quality in Temuco City, Chile, we created and installed a network of inexpensive sensors to detect PM2.5 particulate matter. The 21 measurement points deployed were based on a low-cost Sensiron SPS30 sensor, complemented with temperature and humidity sensors, an Esp32 microcontroller card with LoRa and WiFi wireless communication interface, and a solar charging unit. The units were calibrated using an airtight combustion chamber with a Grimm 11-E as a reference unit. The calibration procedure fits the parameters of a calibration model to map the raw low-cost particle-material measurements into reliable calibrated values. The measurements showed that the concentrations of fine particulate material recorded in Temuco present a high temporal and spatial variability. In critical contamination episodes, pollution reaches values as high as 354 µg/m3, and at the same time, it reaches 50 µg/m3 in other parts of the city. The contamination episodes show a similar trend around the city, and the peaks are in the time interval from 07:00 PM to 1:00 AM. In the winter, this time of day coincides with when families are usually home and there are low temperatures outsideFondo Nacional de Desarrollo Científico y Tecnológico(Chile)Agencia Nacional de Investigación y Desarrollo de ChileCenter of Interventional Medicine for Precision and Advanced Cellular TherapyDepto. de Física de MaterialesFac. de Ciencias FísicasTRUEpubDescuento UC

ZigBee-based wireless sensor network localization for cattle monitoring in grazing fields

This paper presents the design of a localization scheme in wireless sensor networks (WSN) for cattle monitoring applications in grazing fields. No additional hardware was required for distance estimation since they were performed using the link quality indication (LQI), which is a standard feature of the ZigBee protocol. The ratiometric vector iteration (RVI) algorithm was implemented and modified to work with LQI measurements instead of the usual received signal strength indication (RSSI). Experimental results show acceptable localization performance given the requirements of usual cattle monitoring applications at low cost and low power consumption. (C) 2010 Elsevier B.V. All rights reserved