Edge-to-cloud sensing and actuation semantics in the industrial Internet of Things

There are billions of devices worldwide deployed, connected, and communicating to other systems. Sensors and actuators, which can be stationary or movable devices. These Edge devices are considered part of the Internet of Things (IoT) devices, which can be referred to as a tier of the Computing Continuum paradigm. There are two main concerns at stake in the success of this ecosystem. The interoperability between devices and systems is the first. Mainly, because most of them communicate uniquely and differently from each other, leading to heterogeneous data. The second issue is the lack of decision-making capacity to conduct actuations, such as communicating through different computing tiers based on latency constraints due to a certain measured factor. In this article, we propose an ontology to improve device interoperability in the IoT. In addition, we also explain how to ease data communication between Computing Continuum devices, providing tools to enhance data management and decision-making. A use case is also presented, using the automotive industry, where quickness in maneuver determination is key to avoid accidents. It is exemplified using two Raspberry Pi devices, connected using different networks and choosing the appropriate one depending on context-aware conditions.This work is partially funded by: Industrial Doctorates (2019 DI 001) from Generalitat de Catalunya. The SUDOQU project (PID2021-127181OB-I00) from MCIN/AEI. FEDER “Una manera de hacer Europa”; and project 2017-SGR-1749 from Generalitat de Catalunya. Also with the support of inLab FIB at UPC and Worldsensing.Peer ReviewedPostprint (published version

Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration

Future AI applications require performance, reliability and privacy that the existing, cloud-dependant system architectures cannot provide. In this article, we study orchestration in the device-edge-cloud continuum, and focus on AI for edge, that is, the AI methods used in resource orchestration. We claim that to support the constantly growing requirements of intelligent applications in the device-edge-cloud computing continuum, resource orchestration needs to embrace edge AI and emphasize local autonomy and intelligence. To justify the claim, we provide a general definition for continuum orchestration, and look at how current and emerging orchestration paradigms are suitable for the computing continuum. We describe certain major emerging research themes that may affect future orchestration, and provide an early vision of an orchestration paradigm that embraces those research themes. Finally, we survey current key edge AI methods and look at how they may contribute into fulfilling the vision of future continuum orchestration.Comment: 50 pages, 8 figures (Revised content in all sections, added figures and new section

Map-less inventory and location for an RFID-based robot

This thesis presents a new paradigm for RFID-based inventory robots. This map-less operation increases the operative autonomy of the robots as they no longer require a mapping step. This new paradigm is based on the stigmergy concept. Additionally, this new paradigm leads to a simplification of the robot design and allows the cooperation among multiple robots, increasing the robustness and scalability of the system while reducing its cost. The stock-counting problem is defined and an algorithm based on stigmergy is proposed as a solution, which is initially tested in simulation, an later in real scenarios. This thesis details the design process and development of two robots that can take advantage of this new paradigm and that are tested in a real environment, the library of the university. Finally the thesis also presents a new RFID groups location algorithm aligned with the main characteristics of the new paradigm: simplification and efficiency.Aquesta tesi presenta un nou paradigma per als robots d'inventari basats en RFID. Aquest no requereix un mapa de l'entorn, així s'augmenta l'autonomia operativa dels robots. El nou paradigma està basat en el concepte d'estigmergia. A més, permet la simplificació del disseny dels robots, i de manera inherent, la coordinació entre ells. Així, la robustesa i l'adaptabilitat del sistema augmenta a la vegada que el cost es veu reduït. La tesi descriu el problema de ``stock-counting'' i proposa un algorisme com a solució, inicialment es desenvolupa i prova en una simulació basada en grafs. També es detalla el procés de disseny de dos robots per aprofitar els avantatges d'aquest nou paradigma. Els robots són provats a la biblioteca de la universitat, obtenint uns resultats molt satisfactoris. Finalment, es presenta un algorisme de localització de grups d'etiquetes RFID que s'alinea amb les característiques del nou paradigma: simplicitat i eficiència

Map-less inventory and location for an RFID-based robot

This thesis presents a new paradigm for RFID-based inventory robots. This map-less operation increases the operative autonomy of the robots as they no longer require a mapping step. This new paradigm is based on the stigmergy concept. Additionally, this new paradigm leads to a simplification of the robot design and allows the cooperation among multiple robots, increasing the robustness and scalability of the system while reducing its cost. The stock-counting problem is defined and an algorithm based on stigmergy is proposed as a solution, which is initially tested in simulation, an later in real scenarios. This thesis details the design process and development of two robots that can take advantage of this new paradigm and that are tested in a real environment, the library of the university. Finally the thesis also presents a new RFID groups location algorithm aligned with the main characteristics of the new paradigm: simplification and efficiency.Aquesta tesi presenta un nou paradigma per als robots d'inventari basats en RFID. Aquest no requereix un mapa de l'entorn, així s'augmenta l'autonomia operativa dels robots. El nou paradigma està basat en el concepte d'estigmergia. A més, permet la simplificació del disseny dels robots, i de manera inherent, la coordinació entre ells. Així, la robustesa i l'adaptabilitat del sistema augmenta a la vegada que el cost es veu reduït. La tesi descriu el problema de ``stock-counting'' i proposa un algorisme com a solució, inicialment es desenvolupa i prova en una simulació basada en grafs. També es detalla el procés de disseny de dos robots per aprofitar els avantatges d'aquest nou paradigma. Els robots són provats a la biblioteca de la universitat, obtenint uns resultats molt satisfactoris. Finalment, es presenta un algorisme de localització de grups d'etiquetes RFID que s'alinea amb les característiques del nou paradigma: simplicitat i eficiència

Stock visibility for retail using an RFID robot

Purpose - The combination of the latest advancements in Information and Communication Technolo- gies (ICT) with the latest developments in AutoID technologies, especially Radio Frequency Identification (RFID), brings the possibility of high-resolution, item-level visibility of the entire supply chain. In the particular case of retail, visibility of both the stock count and item location in the shop oor is crucial not only for an effective management of the retail supply chain, but also for physical retail stores to compete with on-line retailers. We propose an autonomous robot that can perform stock-taking using RFID for item level identification much more accurately and efficiently than the traditional method of using human operators with RFID handheld readers. Design/methodology/approach - This work follows the design science methodology. The article highlights a required improvement for an RFID inventory robot. The design hypothesis leads to a novel algorithm. Then the cycle of development and evaluation is iterated several times. Finally, conclusions are derived and a new basis for further development is provided. Findings - An autonomous robot for stock-taking is proven feasible. By applying a proper navigation strategy, coupled to the stream of identifications, the accuracy, precision, consistency and time to complete stock-taking are significantly better than doing the same task manually. Research limitations/implications - The main limitation of this work is the unavailability of data to analyse the actual impact on the correction of Inventory Record Inaccuracy (IRI) and its subsequent implications for supply chain management. Nonetheless, it is shown that figures of actual stock-tacking procedures can be significantly improved. Originality/value - This paper discloses the potential of deploying an inventory robot in the supply chain. The robot is called to be a key source of inventory data conforming item-level, high-resolution supply chain management and omnichannel retail. Theoretical/scientific contribution - The paper shows that a fully automated inventory process with an accuracy above 99% is possible combining RFID and autonomous robot technologies. Managerial contribution - This paper shows the managers of traditional retail chains how they can obtain in a cost-effective way a high resolution visibility of the stock in the retail oor. This visibility is necessary in order to both manage the supply chain more efficiently, and to implement the omnichannel processes necessary to remain competitive with respect to on-line retailers

Autonomous stock counting based on a stigmergic algorithm for multi-robot systems

Maintaining an accurate and close to real time inventory of items is crucial for an efficient Supply Chain Management (SCM), which is one of the main pillars of successful business decisions in the retail market. Due to theft and misplacement, perpetual inventory systems are not enough for having an accurate picture of the current inventory. However, even if the retailer has implemented an RFID-based solution, manual inventories using handheld RFID readers tend to be tedious, expensive and inaccurate. Therefore, a solution that can autonomously take inventories with high accuracy is expected to have a great impact in the market. One of the most promising possibilities of automatic inventories are inventory RFID-based robots. However, current inventory robots are not yet fully autonomous. This article proposes a fully autonomous solution for an inventory robot that, in addition, can be implemented in very simple robots reducing its cost and therefore its entrance barrier. The article first defines the problem of stock counting and a solution based on a multi-robot system is proposed. The algorithm developed determines the state of the problem using the same RFID tags that retailers add to their items, so they can guide the robot through a complete stock counting task. Simulation and tests in a real environment, a university library, validate the developed algorithm and its application for multi-robot systems obtaining accuracy figures as high as 99.5% of accuracy.Co-funded by the Spanish Ministry of Economy and Competitiveness under the María de Maeztu Units of Excellence Program (MDM-2015-0502

Development of an RFID Inventory Robot (AdvanRobot)

AdvanRobot proposes a new robot for inventorying and locating all the products inside a retail store without the need of installing any fixed infrastructure. The patent pending robot combines a laser-guided autonomous robotic base with a Radio Frequency Identification (RFID) payload composed of several RFID readers and antennas, as well as a 3D camera. AdvanRobot is able not only to replace human operators, but to dramatically increase the efficiency and accuracy in providing inventory, while also adding the capacity to produce store maps and product location. Some important benefit of the inventory capabilities of AdvanRobot are the reduction in stock-outs, which can cause a drop in sales and are the most important source of frustration for customers; the reduction of the number of items per reference maximizing the number of references per square meter; and reducing the cost of capital due to over-stocking [1, 7]. Another important economic benefit expected from the inventorying and location capabilities of the robot is the ability to efficiently prepare on-line orders from the closest store to the customer, allowing retailers to compete with the likes of Amazon (a.k.a. omnichannel retail). Additionally, the robot enables to: produce a 3D model of the store; detect misplaced items; and assist customers and staff in finding products (wayfinding)