10 SMEs have been added in the IoT-NGIN family to benefit from IoT-NGIN innovations!
The new participants have been selected after the evaluation of proposals submitted in our 2nd Open Call and will start a “DESIGN-EXPERIMENT-GROWTH” stages’ programme, which will identify the prize winner.
The 10 projects entering IoT-NGIN for demonstrating the project’s functionalities through new applications and services include:
- The Privacy information delivery system for Smart Cities (PrivCity) by Conveqs Oy (Conveqs), Finland. The project aims to address both the safety potential and the privacy concerns of AI enabled cameras in public areas through an easily accessible information system providing citizen-centric information through citizens’ devices, exploiting IoT-NGIN tools. The planned information delivery system will be validated in a real environment at Jätkäsaari, Helsinki.
- The Improved support for Decentralized Identifiers and Verifiable Credentials (Imperial) by Internet Security and Privacy Solutions P.C. (ExcID), Greece. IMPERIAL is motivated by a growing number of research efforts that challenge existing authorization systems. It aims to extend the IoT-NGIN authorization component to include fine-grain access control policies and improve IoT-NGIN’s identity management component by integrating the latest specifications of the did:self DID method[1], which leverages group communication, and support for flexible trust relationships, e.g., delegation.
- The machine-Learning Edge Enabled Autonomous tree inFection detection (LEEAF), by Spark Works Limited (Sparks), Ireland. LEEAF aims to use state-of-the-art technologies including computer vision, machine learning, artificial intelligence, and Unmanned Aircraft Systems (UASs) to facilitate the process of inspecting olive groves regardless of their size or location. LEEAF can thus help olive farmers target treatments and increase profitability. Using drones, multi-spectral cameras, and remote sensors, olive farmers can make accurate nutrient predictions, target phytosanitary treatments, and precisely apply fertilisers and irrigation.
- The Open-Source Private 5G Network solution for Industry4.0 applications (Private5G) by Allbesmart LDA (ABS), Portugal. Combining Private 5G Networks with AI-enabled Edge computing creates tremendous opportunities for advanced Industrial IoT applications. Allbesmart aims to leverage its OpenAirInterface (OAI) deep expertise to build and offer a 5G base station (gNB), integrated with a 5G core network (5GCN), as a plug-and-play and easy-to-use commercial solution running in a single x86 computer platform. In order to achieve this, Private5G will develop a Private 5G Network Management Platform working as an abstraction layer to monitor and control the 5G Radio Access Network (RAN) and the 5GCN, as well as experiment and validate the Private 5G Network prototype in the IoT-NGIN Smart Industry Living Lab.
- The IoT-Enabled Demand-Response Analytics for Energy Communities (IoT-DRACO) by COMSENSUS, komunikacije in senzorika, d.o.o. (COMSENSUS d.o.o.). The project aims to design, implement, enhance, and evaluate novel human-centric methodologies and services focusing on real-time active monitoring and control for data-driven energy communities via next generation IoT enablers. IoT-DRACO aspires to increase local and system energy efficiency, stability and security while minimizing impact on comfortability. To achieve this, IoT-DRACO will compile a next generation IoT DR-enabled energy community specification and architecture, including a generic digital twin to be used with NGSI-LD dataspaces Open API. The solution will implement: Observability and analysis of local grid, energy sources and IoT context; Semi-autonomous real-time actuation and control; Optimization and activation; Security, data integrity, privacy and sharing.
- The Combating fake reviews of physical locations and venues via decentralized proof-of-location (BeenThere) by NEXUSIT Ltd. (Nexus), Bulgaria. The project aims to build trust in user reviews for physical establishments, venues and services. The project seeks to help combat review bombings by offering additional verification that a reviewer has actually visited the physical establishment prior or during the review. The project aims to be implemented as a standalone mobile application that aggregates and enhances reviews from existing platforms.
- The Traffic Prediction using Augmented Reality (TIARA) by DOTSOFT INTEGRATED INTERNET APPLICATIONS AND DATABASES SOCIETE ANONYME (DOTSOFT), Greece. TIARA aims at tackling the problem of forecasting traffic congestions and making recommendations for optimal routes for car drivers, while delivering the “forecast message” using augmented reality technology. This project explores the opportunity behind the big amount of data from various sources (radars, cameras, weather, public transport, etc.), stored into data hubs and deploying machine learning algorithms, to derive predictions for traffic. Traffic prediction will be achieved via forecasting the volume and density of traffic flow, for managing the movement of vehicles, to reduce congestion and recommend optimal routes.
- An innovative system for reliable control of parking lots through a user-friendly interface (AVERATO Park) by QUANTERALL (QTL), Bulgaria. It suggests an innovative system for reliable control of parking lots through a user-friendly interface. It is a smart and sustainable solution in the IoT infrastructure. AVERATO is a platform that connects various points of sale (like virtual POS, QR codes or IoT devices) with payment providers, merchants and end users. The goal of the AVERATO Park project is to develop and implement a new IoT module for contactless payments in parking facilities by using innovative IoT applications that use heterogeneous IoT and IoT-NGIN components.
- The Trusted Uncrewed Aviation Systems Command and Control Based on the Internet of Things (IoT UAS C2) by Flyvercity Ltd (Flyvercity), Israel. The project will explore the application of the IoT-NGIN environment to support UAS advanced operations, including urban flights and beyond-visual-line-of-sight flights. It will also include multiple test flight as a part of experimental activities. A data measurement campaign will be conducted providing value data on the cellular signal behaviour above the ground. Within the project, mechanisms will be explored, that are required to ensure aviation-grade connectivity performance, guaranteed characteristics and proper security.
- The TensyHub by Visign Ltd (Visign), Bulgaria. TensyHub is a wireless sensor network for in situ Structural Health Monitoring ( SHM ) of textile and composite structures. The TensyHub network will be a practical step forward to the idea of a smart city. The structural engineers will have the opportunity to monitor their creations in the same way the car industry follows the lifecycle of its products. In the long term, the Big Data analysis will provide objective feedback for the whole industry. TensyHub will provide the hardware and access to collected data on a subscription basis to facility owners, structural engineers and researchers. A maintenance advisor service will use said data to point to a prompt and targeted inspection of monitored objects.
References
[1] ExcID, “did:self method specification,” available at https://github.com/excid-io/did-self