Logistics and Agri\u2010Food: Digitization to Increase Competitive Advantage and Sustainability. Literature Review and the Case of Italy

This paper examines the current challenges faced by logistics with a focus on the agri\u2010food sector. After outlining the context, a review of the literature on the relationship between logistics and strategic management in gaining and increasing competitiveness in the agri\u2010food sector is con-ducted. In particular, the flow of the paper is as follows: after examining the aforementioned managerial problem and its broader repercussions, the paper proceeds to address two main research questions. First, how and by which tools can digitization contribute to improving supply chain management and sustainability in logistics? Second, what are the main managerial and strategic implications and consequences of this for the agri\u2010food sector in terms of efficiency, effectiveness, cost reduction, and supply chain optimization? Finally, the paper presents Italy as a case study, chosen both for its peculiar internal differences in logistical infrastructures and entrepreneurial management between Northern and Southern regions (which could be at least partially overcome with the use of new technologies and frameworks) and for the importance of the agri\u2010food sector for the domestic economy (accounting about 25% of the country\u2019s GDP), on which digitization should have positive effects in terms of value creation and sustainability

Dimensional discoveries: unveiling the potential of 3D heritage point clouds with a robust ontology framework

3D point clouds feature valuable geometric and, often, radiometric and semantic information to support studies, analyses and understanding of the surveyed scene. Due to their generally large size, the use and interpretation of point clouds could be problematic. User-friendly and quick approaches for querying these valuable datasets and retrieving information could surely support end-users, in particular in the heritage sector. This work presents an ontology-based approach to facilitate the query and use of 3D heritage point clouds by means of sets of rules in order to infer properties and characteristics of the surveyed scene. Our approach is focused on linking together 3D spatial data and expert knowledge, in a way that the ontology can elaborate, represent, enrich and query a given point cloud. Results show how different queries can be set-up and how the procedure can be replicated to various queries and datasets

Principali tecniche e strumenti per il rilievo tridimensionale in ambito archeologico

The increase of 3D acquisition and modeling techniques applied to archeology is due principally to (i) their capacity to survey archeological artifacts with high precision and a non-contact approach and (ii) the possibility to create 3D digital models useful for data analysis, simulation and preservation. These benefits in terms of knowledge oblige the contemporary archaeologist to acquire a better understanding of 3D acquisition and modeling principles and practice. This evidence arises from the necessity of adopting a common language for experts in 3D data management and archaeologists with the principal aim being the understanding of each other’s requirements and sharing of the purposes of the project. In this article the authors propose a concise but exhaustive explanation of the working principles of active and passive 3D acquisition techniques. For each one a description of instruments and methodologies is developed, pointing out pros and cons of every technique. In conclusion, a sensor fusion approach is presented as an interesting solution to increase the instrument performances while obtaining at the same time a quality improvement of 3D acquisition and modeling results. A final multi-resolution application about Pompeii Forum 3D modeling follows and closes the article

Dimensional discoveries: Unveiling the potential of 3d heritage point clouds with a robust ontology framework

3D point clouds feature valuable geometric and, often, radiometric and semantic information to support studies, analyses and understanding of the surveyed scene. Due to their generally large size, the use and interpretation of point clouds could be problematic. User-friendly and quick approaches for querying these valuable datasets and retrieving information could surely support end-users, in particular in the heritage sector. This work presents an ontology-based approach to facilitate the query and use of 3D heritage point clouds by means of sets of rules in order to infer properties and characteristics of the surveyed scene. Our approach is focused on linking together 3D spatial data and expert knowledge, in a way that the ontology can elaborate, represent, enrich and query a given point cloud. Results show how different queries can be set-up and how the procedure can be replicated to various queries and datasets

Principali tecniche e strumenti per il rilievo tridimensionale in ambito archeologico

The increase of 3D acquisition and modeling techniques applied to archeology is due principally to (i) their capacity to survey archeological artifacts with high precision and a non-contact approach and (ii) the possibility to create 3D digital models useful for data analysis, simulation and preservation. These benefits in terms of knowledge oblige the contemporary archaeologist to acquire a better understanding of 3D acquisition and modeling principles and practice. This evidence arises from the necessity of adopting a common language for experts in 3D data management and archaeologists with the principal aim being the understanding of each other’s requirements and sharing of the purposes of the project. In this article the authors propose a concise but exhaustive explanation of the working principles of active and passive 3D acquisition techniques. For each one a description of instruments and methodologies is developed, pointing out pros and cons of every technique. In conclusion, a sensor fusion approach is presented as an interesting solution to increase the instrument performances while obtaining at the same time a quality improvement of 3D acquisition and modeling results. A final multi-resolution application about Pompeii Forum 3D modeling follows and closes the article

AUTOMATED AND ACCURATE ORIENTATION OF COMPLEX IMAGE SEQUENCES

The paper illustrates an automated methodology capable of finding tie points in different categories of images for a successive orientation and camera pose estimation procedure. The algorithmic implementation is encapsulated into a software called ATiPE. The entire procedure combines several algorithms of both Computer Vision (CV) and Photogrammetry in order to obtain accurate results in an automated way. Although there exist numerous efficient solutions for images taken with the traditional aerial block geometry, the complexity and diversity of image network geometry in close-range applications makes the automatic identification of tie points a very complicated task. The reported examples were made available for the 3D-ARCH 2011 conference and include images featuring different characteristics in terms of resolution, network geometry, calibration information and external constraints (ground control points, known distances). In addition, some further examples are shown, that demonstrate the capability of the orientation procedure to cope with a large variety of block configurations

Evaluating tie points distribution, multiplicity and number on the accuracy of UAV photogrammetry blocks

Image orientation is a fundamental task in photogrammetric applications and it is performed by extracting keypoints with hand-crafted or learning-based methods, generating tie points among the images and running a bundle adjustment procedure. Nowadays, due to large number of extracted keypoints, tie point filtering approaches attempt to eliminate redundant tie points in order to increase accuracy and reduce processing time. This paper presents the results of an investigation concerning tie points impact on bundle adjustment results. Simulations and real data are processed in Australis and DBAT to evaluate different affecting factors, including tie point numbers, location accuracy, distribution and multiplicity. Achieved results show that increasing the amount of tie points improve the quality of bundle adjustment results, provided that the tie points are well-distributed on the image. Furthermore, bundle adjustment quality is improved as the multiplicity of tie points increases and their location uncertainty decrease. Based on simulation results, some suggestions for accurate tie points filtering in typical UAV photogrammetry blocks cases are derived