UHF-RFID solutions for logistics units management in the food supply chain

The availability of systems for automatic and simultaneous identification of several items belonging to a logistics unit during production, warehousing and delivering can improve supply chain management and speed traceability controls. Radio frequency identification (RFID) is a powerful technique that potentially permits to reach this goal, but some aspects as, for instance, food product composition (e.g. moisture content, salt or sugar content) and some peculiarities of the production environment (high moisture, high/low temperatures, metallic structures) have prevented, so far, its application in food sector. In the food industry, composition and shape of items are much less regular than in other commodities sectors. In addition, a wide variety of packaging, composed by different materials, is employed. As material, size and shape of items to which the tag should be attached strongly influence the minimum power requested for tag functioning, performance improvements can be achieved only selecting suitable RF identifier for the specific combination of food product and packaging. When dealing with logistics units, the dynamic reading of a vast number of tags originates simultaneous broadcasting of signals (tag-to-tag collisions) that could affect reading rates and the overall reliability of the identification procedure. This paper reports the results of an extensive analysis of the reading performance of UHF RFID systems for multiple dynamic electronic identification of food packed products in controlled conditions. Products were considered singularly or arranged on a logistics pallet. The effects on reading rate and reading zone of different factors, among which the type of product, the number and position of antennas, the field polarization, the reader RF power output, the interrogation protocol configuration as well as the transit speed, the number of tags and their interactions were analysed and compared

Radio frequency identification technologies for livestock management and meat supply chain traceability

Barge, P., Gay, P., Merlino, V. and Tortia, C. 2013. Radio frequency identification technologies for livestock management and meat supply chain traceability. Can. J. Anim. Sci. 93: 23–33. Animal electronic identification could be exploited by farmers as an interesting opportunity to increase the efficiency of herd management and traceability. Although radio frequency identification (RFID) solutions for animal identification have already been envisaged, the integration of a RFID traceability system at farm level has to be carried out carefully, considering different aspects (farm type, number and species of animals, barn structure). The tag persistence on the animal after application, the tag-to-tag collisions in the case of many animals contemporarily present in the reading area of the same antenna and the barn layout play determinant roles in system reliability. The goal of this paper is to evaluate the RFID identification system performance and determine the best practice to apply these devices in livestock management. RFID systems were tested both in laboratory, on the farm and in slaughterhouses for the implementation of a traceability system with automatic animal data capture. For this purpose a complete system for animal identification and tracking, accomplishing regulatory compliance as well as supply chain management requirements, has been developed and is described in the paper. Results were encouraging for identification of calves both in farms and slaughterhouses, while in swine breeding, identification was critical for small piglets. In this case, the design of a RFID gate where tag-to-tag collisions are avoided should be envisaged. </jats:p

Radio Frequency IDentification for meat supply-chain digitalisation

Digitalised supply-chain traceability systems can offer wide prospects both for improving safety as well as enhancing perceived quality. However, the coupling between physical goods and information is often difficult for agri-food items. A solution could be the use of RFID (Radio Frequency IDentification) systems. Due to its wide reading range, Ultra-High Frequency (UHF) technology is already widely used in logistics and warehousing, mostly for the identification of batches of items. A growing interest is also emerging in Near Field Communication (NFC), as several smartphones embed an integrated NFC antenna. This paper deals with the automatic identification of meat products at item level, proposing and evaluating the adoption of different RFID technologies. Different UHF and NFC solutions are proposed, which benchmark tag performances in different configurations, including four meat types (fatty beef, lean beef, chicken and pork), by using a specifically designed test bench. As avoiding the application of two different tags could be advantageous, dual frequency devices (UHF and NFC) are also considered. Significant differences in tag performances, which also depend on meat type and packaging, are highlighted. The paper highlights that tag positioning should consider the geometry of the packaging and the relative positioning of tag, meat and reader antenna

Cost-effective visual odometry system for vehicle motion control in agricultural environments

In precision agriculture, innovative cost-effective technologies and new improved solutions, aimed at making operations and processes more reliable, robust and economically viable, are still needed. In this context, robotics and automation play a crucial role, with particular reference to unmanned vehicles for crop monitoring and site-specific operations. However, unstructured and irregular working environments, such as agricultural scenarios, require specific solutions regarding positioning and motion control of autonomous vehicles. In this paper, a reliable and cost-effective monocular visual odometry system, properly calibrated for the localisation and navigation of tracked vehicles on agricultural terrains, is presented. The main contribution of this work is the design and implementation of an enhanced image processing algorithm, based on the cross-correlation approach. It was specifically developed to use a simplified hardware and a low complexity mechanical system, without compromising performance. By providing sub-pixel results, the presented algorithm allows to exploit low-resolution images, thus obtaining high accuracy in motion estimation with short computing time. The results, in terms of odometry accuracy and processing time, achieved during the in-field experimentation campaign on several terrains proved the effectiveness of the proposed method and its fitness for automatic control solutions in precision agriculture applications