Autonome Sensorsysteme in der Transport- und Lebensmittellogistik

A concise supervision of food products during transport is an essential precondition for the improvement of their quality and reduction of losses. However, existing remote or telemetric systems implement only parts of the entire supervision task. Standard systems measure temperature only at one or two points, and the evaluation of sensor data has to be done manually. This thesis presents a system which measures a spatial profile of temperature and other parameters. The idea of remote transport supervision is extended to a self-contained sensor system that locally processes measurement data and detects critical situations autonomously. The algorithms for sensor data evaluation are implemented inside the means of transport; they can either share a common embedded processor unit or run separately on wireless sensors nodes, which are attached to the loaded freight objects. The system automatically adapts the supervision process to different kinds of goods. This intelligent container combines technologies from different fields, such as RFID, wireless sensor networks, and telemetric system, which have so far been applied separately. A shelf life model, based on the dynamic temperature profile, estimates the amount of quality loss during transport. The quality supervision is implemented as a set of software agents. Each freight object is supervised by an individual sensory way bill . A demonstration system for the supervision of food transports shows the feasibility of this new approach

Spatial temperature profiling by semi-passive RFID loggers for perishable food transportation

Perishable food products are at risk of suffering various damages along the cold chain. The parties involved should control and monitor the conditions of goods in order to ensure their quality for consumers and to comply with all legal requirements. Among environmental parameters during transport, temperature is the most important in prolonging the shelf life of the products. Radio Frequency IDentification (RFID) is an emergent technology that has proven its suitability for tracking and tracing in logistics. This paper shows how miniaturized RFID temperature loggers can be adapted to analyze the amount of local deviations, detect temperature gradients, and estimate the minimum number of sensors that are necessary for reliable monitoring inside a truck or container. These devices are useful tools for improving the control during the transport chain and detecting weaknesses by identifying specific problem areas where corrective actions are necessitated. In a first step, the RFID tags were tested by studying the temperature distribution in a pallet. Then, 15 shipments from a wholesale company in Germany in compartmented trucks were monitored, covering different temperature range conditions. During transport, several temperature differences were found in the same compartment. Using a factorial Analysis of Variance (ANOVA) the influence of different factors has been studied, such as: the location of the logger, type of truck, and external temperature. The shelf life, or keeping quality model, was applied to the recorded temperature profiles. Suggestions for future research areas are also discussed

Uso de membrana amniótica como cobertura temporal en pacientes con quemaduras del hospital Luis Vernaza.

El paciente con quemaduras demanda de un manejo complejo, y el uso de membrana amniótica como cobertura temporal conforma un método muy valioso para favorecer su evolución. Este método forma parte de las alternativas terapéuticas en la Unidad de Quemados del hospital Luis Vernaza (HLV). Objetivos: demostrar la eficiencia del amnios humano como cobertura temporal en pacientes con quemaduras. Metodología: se presenta una serie de 14 casos de pacientes con quemaduras de menos del 25 % de superficie corporal total, tratados en la Unidad de Quemados del HLV, donde se aplicó membrana amniótica humana. Resultados: el 100 % de los pacientes requirió solo de una aplicación, 9 pacientes fueron del sexo masculino (64 %) y 5 del femenino (36 %), con un rango de edades entre 25 y 86 años. La media de edad fue 45 años y mediana de 47 años, la causa de lesión más frecuente fue a causa de flama con 9 casos (64 %). El promedio de estancia hospitalaria postoperatoria fue de 9 días, con un límite inferior de 6 y superior de 13. En ningún paciente se observó signos de infección o rechazo inmunológico y en todos se observó re-epitelización de las lesiones. En la escala de valoración numérica del dolor (del 1 al 10), se confirmó que todos los pacientes referían menos dolor y posteriormente al día 7 desapareció en todos. Discusión: el uso de membrana amniótica humana en pacientes quemados evita la pérdida de líquidos, electrolitos y proteínas en las áreas cruentas, a modo de barrera artificial ayuda a prevenir las infecciones especialmente, como una membrana basal sustituta, sin desmerecer la importancia del efecto analgésico sobre las lesiones

Performance of ZigBee-based wireless sensor nodes for real-time monitoring of fruits logistics

Progress in fruit logistics requires an increasing number of measurements to be performed in refrigerated chambers and during transport. Wireless sensor networks (WSN) are a promising solution in this field. This paper explores the potential of wireless sensor technology for monitoring fruit storage and transport conditions. It focuses in particular on ZigBee technology with special regard to two different commercial modules (Xbow and Xbee). The main contributions of the paper relate to the analysis of battery life under cooling conditions and the evaluation of the reliability of communications and measurements. Psychrometric equations were used for quick assessment of changes in the absolute water content of air, allowing estimation of future water loss, and detection of condensation on the product

Interpolation of spatial temperature profiles by sensor networks

The monitoring of spatial profiles of a physical property such as temperature becomes feasible with the decreasing cost of wireless sensor nodes. But to obtain a temperature value for each point in space, it is necessary to interpolate between the existing sensor positions. Accurate spatial temperature supervision is a crucial precondition for maintaining high quality standards in the transportation of food products. The Kriging method was programmed for the ARM processor of the iMote2 sensor nodes and tested with 14 experimental data sets that were recorded in cold storage rooms and transports in trucks and containers. The error of the interpolation by Kriging was 20% lower than the simpler inverse-distance-weighting used as a reference metho

Application of Neurocomputing for Data Approximation and Classification in Wireless Sensor Networks

A new application of neurocomputing for data approximation and classification is introduced to process data in a wireless sensor network. For this purpose, a simplified dynamic sliding backpropagation algorithm is implemented on a wireless sensor network for transportation applications. It is able to approximate temperature and humidity in sensor nodes. In addition, two architectures of “radial basis function” (RBF) classifiers are introduced with probabilistic features for data classification in sensor nodes. The applied approximation and classification algorithms could be used in similar applications for data processing in embedded systems