Δημοσιότητα

Επιστημονικές Δημοσιεύσεις

  • Τσακιρίδης Σωτήριος, Πληροφορικός – Γεωπόνος, sotiris@serres.gr
  • Τσιμπίρης Αλκιβιάδης, Αναπληρωτής Καθηγητής, atsimpiris@ihu.gr
  • Βαρσάμης Δημήτριος, Καθηγητής, dvarsam@ihu.gr

ΠΕΡΙΛΗΨΗ: Η καταμέτρηση προϊόντων σε έναν υπαίθριο ή στεγασμένο αποθηκευτικό χώρο βασίζεται στην εκ των προτέρων γνώση των διαστάσεων της παλέτας. Τα δεδομένα εισόδου είναι ένα νέφος τρισδιάστατων σημείων τα οποία δημιουργούνται από τρισδιάστατους σαρωτές (LIDAR) προσαρμοσμένους σε εναέρια μέσα (drones). Για τους σκοπούς της έρευνας έχει υλοποιηθεί ένας προσομοιωτής αποθήκης στην γλώσσα python (έκδοση 3.9). Στην πρώτη φάση της έρευνας εξετάζεται η ιδανική περίπτωση διασποράς των σημείων στο χώρο με ακέραιες τιμές συντεταγμένων και με μία μονάδα μήκους να αντιστοιχεί στην απόσταση μεταξύ δύο γειτονικών pixels κατά την οριζόντια ή κατακόρυφη διεύθυνση. Σε επόμενο στάδιο της έρευνας θα τροποποιηθεί ο γεννήτορας τρισδιάστατων σημείων ώστε να παράγονται πιο ρεαλιστικά μοντέλα αποθήκης και θα προταθούν βελτιωμένες εκδόσεις των υφιστάμενων αλγορίθμων που να λαμβάνουν υπόψη τις διακυμάνσεις του ύψους. 

  • Sotirios Tsakiridis, Department of Computer, Informatics and Telecommunications Engineering, International Hellenic University
  • Apostolos Papakonstantinou, Department of Civil Engineering and Geomatics Cyprus University of Technology
  • Alexandros Kapandelis, Department of Computer, Informatics and Telecommunications Engineering International Hellenic University
  • Paris Mastorocostas, Dept. Informatics and Computer Engineering University of West Attica
  • Alkiviadis Tsimpiris, Department of Informatics, Computer and Telecomunications Engineering International Hellenic University
  • Dimitrios Varsamis, Department of Computer, Informatics and Telecommunications Engineering, International Hellenic University

ABSTRACT: The computational estimation of an indoor or open-space warehouse inventory is based on the prior knowledge of the pallet dimensions. The input data consist of a three-dimensional point-cloud created by three dimensional (3D) scanners (LiDAR technology) adapted to aerial vehicles (Drones). For research purposes, a storage simulator has been implemented in the Python language (version 3.9). In the first phase, this research focuses on the ideal case of point-dispersion, with integer values for coordinates, in which a unit length corresponds to the distance between two neighboring pixels in the horizontal or vertical direction. In a subsequent stage, the generator of three-dimensional points will be modified to produce more realistic warehouse models. Improved versions of existing algorithms will be proposed, taking into consideration the height variations.

  • Sotirios Tsakiridis, Dept. Computer, Informatics and Telecommunications Engineering International Hellenic University
  • Apostolos Papakonstantinou, Dept. Civil Engineering and Geomatics Cyprus University of Technology
  • Alexandros Kapandelis, Dept. Computer, Informatics and Telecommunications Engineering International Hellenic University
  • Paris Mastorocostas, Dept. Informatics and Computer Engineering University of West Attica
  • Alkiviadis Tsimpiris, Dept. Computer, Informatics and Telecommunications Engineering International Hellenic University
  • Dimitrios Varsamis, Dept. Computer, Informatics and Telecommunications Engineering International Hellenic University

ABSTRACT: The advancement of technology has brought about a revolution in industrial operations, where specialized tools play a crucial role in enhancing efficiency. This study delves into the significant impact of the logistics department in global industries and proposes an innovative solution for inventory detection and recognition using unmanned aerial vehicles (UAVs) equipped with LiDAR technology. Unlike existing research that often involves intricate hardware systems and algorithms leading to increased costs and computational demands, our research focuses on streamlining the inventory detection process by utilizing a LiDAR data and an algorithmic approach that minimizes the time of extensive counting process into the warehouse to quantify the pallets existing. The proposed methodology entails a custom-made quadcopter equipped with a single-beam and high-frequency LiDAR range finder. Operating autonomously along a predeter-mined flight plan, the drone captures high-frequency range data of warehouse inventory. The paper comprehensively outlines the UAV control procedures, warehouse scanning using LiDAR, and the inventory detection and quantification of pallets algorithmic process. The proposed method processes LiDAR data in a post process way, estimating the number of pallets and, consequently, producing a map of each stack within the warehouse denoting the quantities of pallets. The research results showcase the successful implementation of the proposed approach in a model warehouse, achieving an impressive 100% evaluation accuracy. Future research endeavors aim to extend this methodology to warehouses with dynamic product placements, emphasizing real-time monitoring for comprehensive inventory detection. This innovative approach stands out as a cost-effective and efficient solution for industries seeking accurate and timely inventory information.

  • SOTIRIOS TSAKIRIDIS, International Hellenic University
  • APOSTOLOS PAPAKONSTANTINOU, Department of Civil Engineering and Geomatics Cyprus University of Technology
  • ALEXANDROS KAPANDELIS, Department of Computer, Informatics and Telecommunications Engineering International Hellenic University
  • PARIS MASTOROCOSTAS, Department OF Informatics and Computer Engineering University of West Attica
  • ALKIVIADIS TSIMPIRIS, International Hellenic University
  • DIMITRIOS VARSAMIS, International Hellenic University

ABSTRACT: The advancement of technology has brought about a revolution in industrial operations, where specialized tools play a crucial role in enhancing efficiency. This study delves into the significant impact of the logistics department in global industries and proposes an innovative solution for inventory detection and recognition using unmanned aerial vehicles (UAVs) equipped with LiDAR technology. Unlike existing research that often involves intricate hardware systems and algorithms leading to increased costs and computational demands, our research focuses on streamlining the inventory detection process by utilizing a LiDAR data and an algorithmic approach that minimizes the time of extensive counting process into the warehouse to quantify the pallets existing. The proposed methodology entails a custom-made quadcopter equipped with a single-beam and high-frequency LiDAR range finder. Operating autonomously along a predetermined flight plan, the drone captures high-frequency range data of warehouse inventory. The paper comprehensively outlines the UAV control procedures, warehouse scanning using LiDAR, and the inventory detection and quantification of pallets algorithmic process. The proposed method processes LiDAR data in a post-process way, estimating the number of pallets and, consequently, producing a map of each stack within the warehouse denoting the quantities of pallets. The research results showcase the successful implementation of the proposed approach in a model warehouse, achieving an impressive 100% evaluation accuracy. Future research endeavors aim to extend this methodology to warehouses with dynamic product placements, emphasizing real-time monitoring for comprehensive inventory detection. This innovative approach stands out as a cost-effective and efficient solution for industries seeking accurate and timely inventory information.

  • SOTIRIOS TSAKIRIDIS
  • ALKIVIADIS TSIMPIRIS
  • ATHANASIOS ANGEIOPLASTIS
  • NIKOLAOS PAPAIOANNOU
  • DIMITRIOS V ARSAMIS

International Hellenic University, Department of Computer, Informatics and Telecommunications Engineering, Serres, Greece

ABSTRACT: This research paper examines the strategic deployment of Oracle APEX by a prominent Greek soft drinks manufacturing enterprise for the enhancement of data warehouse management spanning the period from 2018 to 2022. The integration of Oracle APEX, renowned for its low-code application development capabilities, has emerged as a pivotal catalyst in optimizing data processing workflows, elevating analytical functionalities, and cultivating streamlined decision-making processes within the organization’s data ecosystem. This article delves into the specific benefits and outcomes derived from the adoption of Oracle APEX in the context of data warehousing, shedding light on the transformative impact on the company’s operations.

  • Sotirios Tsakiridis, Dept. Computer, Informatics and Telecommunications Engineering International Hellenic University
  • Alkiviadis Tsimpiris, Dept. Computer, Informatics and Telecommunications Engineering International Hellenic University
  • Athanasios Angeioplastis, Dept. Computer, Informatics and Telecommunications Engineering International Hellenic University
  • Nikolaos Papaioannou, Dept. Computer, Informatics and Telecommunications Engineering International Hellenic University
  • Paris Mastorocostas, Dept. Informatics and Computer Engineering University of West Attica
  • Dimitrios Varsamis, Dept. Computer, Informatics and Telecommunications Engineering International Hellenic University

ABSTRACT: The research focuses on the process of creating a data warehouse to meet the decision-making needs of a Greek beverage company. The data cover the period from 2018 to 2022. The developed data warehouse schema follows the star schema, with one fact table and five-dimension tables. Based on this structure, a web application was developed in PHP, which displays reports, charts, and analyses on the company’s performance through interactive queries. Additionally, prediction functions tailored to the company’s data were developed in Python. The process followed, the queries for creating the data warehouse, as well as the commands for creating analyses and predictions, serve as a useful guide for other companies that wish to upgrade the capabilities of their ERP systems.

  • Sotirios Tsakiridis, Dept. Computer, Informatics and Telecommunications Engineering International Hellenic University
  • Alkiviadis Tsimpiris, Dept. Computer, Informatics and Telecommunications Engineering International Hellenic University
  • Athanasios Angeioplastis, Dept. Computer, Informatics and Telecommunications Engineering International Hellenic University
  • Nikolaos Papaioannou, Dept. Computer, Informatics and
  • elecommunications Engineering International Hellenic University
  • Paris Mastorocostas, Dept. Informatics and Computer Engineering University of West Attica
  • Apostolos Papakonstantinou, Dept Civil Engineering and Geomatics Cyprus University of Technology Lemesos
  • Angeliki Kamilali, Dept. Computer, Informatics and Telecommunications Engineering International Hellenic University
  • Dimitrios Varsamis, Dept. Computer, Informatics and Telecommunications Engineering International Hellenic University

ABSTRACT: In this paper we present the process of optimal placement of industrial products (pallets) in mapped warehouses and specifically in a soft drink company in Greece. The optimization criterion is to minimize the cost of moving the lifting machine that places the products in specific positions. The computational method of optimal placement of industrial products receives data from the automatic product count of the mapped warehouse and from the sales predictive model. Therefore, the computational method, having knowledge of the location and number of products in the warehouse and the prediction of sales for each product, places the products produced in an optimal way. Automatic product counting is carried out using an unmanned aerial vehicle (UAV) which developed and applied in soft drink company in Greece. The sales prediction is carried out through a prediction model which developed in a soft drink company in Greece.