George Routis, Marios Paraskevopoulos, I. Vetsikas, I. Roussaki, D. Stavrakoudis, D. Katsantonis
{"title":"Data-Driven and Interoperable Smart Agriculture: An IoT-based Use-Case for Arable Crops","authors":"George Routis, Marios Paraskevopoulos, I. Vetsikas, I. Roussaki, D. Stavrakoudis, D. Katsantonis","doi":"10.1109/COINS54846.2022.9855001","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9855001","url":null,"abstract":"The sustainability of the agricultural sector relies on exploiting all technologies available today (and further advancing them), in order to decrease the costs and the environmental impact, maintaining yields at the same time. DEMETER is a Horizon 2020 project that aspires to empower farmers to better exploit their existing operational context and create new business models through smart data sharing in the agricultural sector, in an interoperable, reusable, and safe manner. This paper presents a specific use-case that uses the facilities developed in order to optimize rice and maize irrigation and fertilization management processes. It provides an overview of the project’s objectives and concepts and then describes the various modules of the specific use-case and how they cooperate to establish suitable decision support mechanisms. Finally, it elaborates on how the development of other similar services reusing the individual building blocks, in an interoperable and vendor-neutral manner, is facilitated.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127340741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Artem Barger, O. Ilina, Alexander Zemtsov, Ksenia Tagirova
{"title":"Trustful Charity Foundation platform based on Hyperledger Fabric","authors":"Artem Barger, O. Ilina, Alexander Zemtsov, Ksenia Tagirova","doi":"10.1109/COINS54846.2022.9854995","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9854995","url":null,"abstract":"Charity plays a significant role in our society and is considered by many people as the most common way to repay our social debt. Therefore a significant amount of donated funds circulate around the world. In recent years, there has been an increase in the number of non-profit organizations and charitable foundations collecting funds for various charity needs. Unfortunately, the reputation of charity organizations is often undermined by the actions of unscrupulous organizations. Significant reputational damage caused by cases of fraud and corruption reduces the level of trust and decreases the amount of collected funds. We strongly believe that blockchain technology can help charity organizations to build trust, increase efficiency and transparency. We are presenting a blockchain-based charity foundation platform implemented on the top of Hyperledger Fabric. This paper examines the significance of blockchain technology for modern philanthropy. We believe that a blockchain-based platform can mobilize new actors to participate in charity activities by increasing transparency and building trust.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117226437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Deep Learning-Based Smart Assistive Framework for Visually Impaired People","authors":"Y. Muhammad, M. Jan, Spyridon Mastorakis, B. Zada","doi":"10.1109/COINS54846.2022.9854984","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9854984","url":null,"abstract":"According to the World Health Organization (WHO), there are millions of visually impaired people in the world who face a lot of difficulties in moving independently. They always need help from people with normal sight. The capability to find their way to their intended destination in an unseen place is a major challenge for visually impaired people. This paper aimed to assist these individuals in resolving their problems with moving to any place on their own. To this end, we developed an intelligent system for visually impaired people using a deep learning (DL) algorithm, i.e., convolutional neural network (CNN) architecture, AlexNet, to recognize the situation and scene objects automatically in real-time. The proposed system consists of a Raspberry Pi, ultrasonic sensors, a camera, breadboards, jumper wires, a buzzer, and headphones. Breadboards are used to connect the sensors with the help of a Raspberry Pi and jumper wires. The sensors are used for the detection of obstacles and potholes, while the camera performs as a virtual eye for the visually impaired people by recognizing these obstacles in any direction (front, left, and right). The proposed system provides information about objects to a blind person. The system automatically calculates the distance between the blind person and the obstacle that how far he/she is from the obstacle. Furthermore, a voice message alerts the blind person about the obstacle and directs him/her via earphones. The obtained experimental results show that the utilized CNN architecture AlexNet yielded an impressive result of 99.56% validation accuracy and has a validation loss of 0.0201%.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129152012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Saidur Rahman, Apostolos Kalatzis, Mike P. Wittie, David L. Millman, Laura M. Stanley
{"title":"Dynamic Checkpoint Initiation in Serverless MEC","authors":"Saidur Rahman, Apostolos Kalatzis, Mike P. Wittie, David L. Millman, Laura M. Stanley","doi":"10.1109/COINS54846.2022.9855008","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9855008","url":null,"abstract":"Mobile applications may want to offload heavy processing jobs to more powerful nodes. Mobile Edge Computing (MEC) can provide low latency and fast processing for the offloaded jobs. Due to the limited capacity of MEC, an efficient checkpointing mechanism can provide fair resource sharing among offloaded jobs by interrupting them as necessary. It is important for an MEC controller to decide when to start checkpointing based on the resource availability and the number of queued requests. In this paper, we propose a resource management framework that decides when to start checkpointing to utilize the MEC compute resources efficiently. We also show how we can integrate the proposed framework in practical implementation of an MEC architecture.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131930410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xuening Dong, A. Amirsoleimani, M. Azghadi, R. Genov
{"title":"In-Memory Memristive Transformation Stage of Gaussian Random Number Generator","authors":"Xuening Dong, A. Amirsoleimani, M. Azghadi, R. Genov","doi":"10.1109/COINS54846.2022.9855007","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9855007","url":null,"abstract":"In this work, we present a modification to the digital Wallace-based Gaussian Random Number Generator (GRNG) by implementing an in-memory memristive dot-product engine in place of the vector-matrix multiplication (VMM) stage. The dot-product engine provides an analog interface to the GRNG with statistical robustness and better resource efficiency. One modification with three different structures is proposed and evaluated by the statistical test pass rates and benchmarked against the digital implementations. The best-proposed modification achieved a 95.8% test pass rate for 100 iterative small pool generation while requiring 23.6% and 44.4% less power and area consumption.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132010648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Trustworthy SoC Reconfiguration Aimed at Product-Service Systems: a Literature Review","authors":"M. Méré, F. Jouault, Loïc Pallardy, R. Perdriau","doi":"10.1109/COINS54846.2022.9854965","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9854965","url":null,"abstract":"The electronics industry is a field where production is increasingly complex despite very competitive prices. Semiconductor cost production are mainly due to complex infrastructures and high non-recurring development costs. In order to be competitive, integrated circuits (ICs) need to be mass-produced. However, there is a need for a relatively large variety of components to better suit all applications. In addition, the whole logistics process involves numerous actors, and needs to be secured to avoid product theft and counterfeiting. In order to address these problems, proposals have emerged in the literature that allow the management of actions to be carried out throughout the product’s life cycle via hardware modules. These propositions simplify components customization, which is an efficient way to associate mass production and small series. Described as life cycle management systems (LCMS), they enable new applications that could be an environmental asset such as facilitating Product Service Systems (PSS), a more sustainable business model for intelligent objects. they even give guarantees on component traceability over the whole supply chain. In the perspective of determining which already available solutions are capable of meeting requirements that make the implementation of an LCMS on a component, this paper collects a set of research references capable of addressing such expectations. The target is to establish the criteria necessary to meet these requirements and then compare the different solutions in order to determine the most promising ones.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131087671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Koki Fujita, Shugo Fujimura, Yuwei Sun, H. Esaki, H. Ochiai
{"title":"Federated Reinforcement Learning for the Building Facilities","authors":"Koki Fujita, Shugo Fujimura, Yuwei Sun, H. Esaki, H. Ochiai","doi":"10.1109/COINS54846.2022.9854959","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9854959","url":null,"abstract":"In recent years, systems utilizing AI and IoT have been introduced. The development of IoT enhances the relationship between people and things, and convenience is improving. AI is also utilized to automate tasks that have been performed by humans, and to control various tasks. It is also beginning to be applied to building facilities, and there are situations where buildings interact cooperatively with each other. In this paper, we address the issue of controlling building facilities. Buildings are equipped with air conditioners, storage batteries, and solar panels. The goal is to control HVAC system considering the traffic of people and the state of storage batteries. Since each building has different target situations, it is important to find the optimal policies for each building. We aim to solve this problem by using reinforcement learning and to develop a framework that can learn various policies by the simple reward functions. In this study, we have experimentally shown that the control is optimal for power saving scenarios. For building facilities, we proposed various basic reward functions and also confirmed that flexible policies can be learned by combining these functions. Furthermore, we show that the learning convergence can be accelerated by federated learning while preserving privacy among the buildings.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134008455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Packet Classification with Segregated Cross-Producting","authors":"Pi-Chung Wang","doi":"10.1109/COINS54846.2022.9854998","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9854998","url":null,"abstract":"Packet classification, which performs multidimensional point location upon fields in packet headers, is the key technology for enabling software-defined networking (SDN). It categorizes incoming packets into multiple forwarding classes based on pre-defined rules. This categorization also enables quality of service or network security. In this work, we propose an algorithm, Segregated Cross-producting, to improve the scalability of cross-producting in term of storage. The performance of our scheme was evaluated with rule sets of varying sizes and characteristics. The experimental results show that our scheme achieves good and stable performance in terms of speed and space.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134184347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A practical approach to cross-agri-domain interoperability and integration","authors":"Sonia Bilbao-Arechabala, Belén Martínez","doi":"10.1109/COINS54846.2022.9854999","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9854999","url":null,"abstract":"In this paper we describe the process for making sensors and IoT devices interoperable with existing agri-solutions, and to federate data and services between two agricultural smart platforms, more precisely the AFarCloud and DEMETER solutions. This approach is in line with EU data-driven strategy and GAIA-X’s federation strategy. Finally, we present the use case where this process has been tested and validated, i.e. Kotipelto farm, a dairy farm located in Ylivieska (Finland).","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"11 1-2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131923933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Markus Sauer, Andreas Dachsberger, Leonard Giglhuber, Lukasz Zalewski
{"title":"Decentralized Deadlock Prevention for Self-Organizing Industrial Mobile Robot Fleets","authors":"Markus Sauer, Andreas Dachsberger, Leonard Giglhuber, Lukasz Zalewski","doi":"10.1109/COINS54846.2022.9854958","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9854958","url":null,"abstract":"Industrial systems more and more integrate fleets of autonomous mobile robots to perform transport tasks on the shop floor. Nowadays, central fleet management systems control all functionalities like task allocation, path planning and motion planning, which includes collision and deadlock prevention. But with increasing demand for flexibility and the ability to scale, today’s centralized systems reach technical limits. Thus, a trend towards decentralized systems can be observed. Functionality that used to be located in a central unit is delegated to the executing robots, such that every entity in the system gets more intelligent and autonomous.This work targets systems that are in need of a decentralized algorithm for preventing collisions and deadlocks at the start and end points of planned routes. To that end, we presuppose robots that are already able to navigate requested paths and avoid collisions during movement. We propose a new solution to this problem and compare it to an existing decentralized algorithm in a simulated environment. For that we provide requirements, qualitative and quantitative metrics and an evaluation of both algorithms for real-world industrial implementation. Recommendations are given on which algorithm to use given the target objectives of the system.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122566970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}