INGENIOUS aims to design and evaluate the Next-Generation IoT (NG-IoT) solution, with emphasis on 5G and the development of Edge and Cloud computing extensions for IoT, as well as providing smart networking and data management solutions with Artificial Intelligence and Machine Learning (AI/ML). The project embraces the 5G Infrastructure Association (5G IA) and Alliance for Internet of Things Innovation (AIOTI) vision for empowering smart manufacturing and smart mobility verticals.

1. Next-generation IoT Solutions
for the Universal Supply Chain'.
iNGENIOUS CONSORTIUM
@ingenious_iot
ingenious_iot
ingenious_iot
iNGENIOUS has received funding
from the European Union’s Horizon
2020 research and innovation
programme under grant agreement
No 957216"
iNGENIOUS (Next-GENeration IoT sOlutions for the Universal Supply
chain) aims to design and evaluate the Next-Generation IoT (NG-IoT)
solutions, with emphasis on 5G and the development of Edge and
Cloud computing extensions for IoT, as well as providing smart
networking and data management solutions with Artificial Intelligen-
ce and Machine Learning.
For this purpose, the project will exploit some of the most innovative
and emerging technologies in line with the standardised trend, contri-
buting to the NG-IoT and proposing technical and business enablers
to build a complete platform towards the future fully digitized supply
chain management.
Project outcomes will be validated into 4 large-scale Proof of Concept
demonstrations, covering 1 factory in the north of Spain, 2 ports, the
port of Valencia in Spain and the port of Livorno in Italy, and 1 ship
traveling from Valencia in Spain to Piraeus in Greece, encompassing 6
uses cases.
The iNGENIOUS consortium is formed by 21 partners from eight coun-
tries, including telecom vendors and manufacturers, network opera-
tors, logistics partners, universities, research institutes and seven
high-tech SMEs.

2. 5GC
(TSN/NWDAF)
Automated Robot
+ Automated Guided Vehicle
gNB & MEC
Mesh sensor Network
DLT1
DLT2 DLT3
DLT4
DLT5
M2M1
M2M2
M2M3 M2M4
M2M5
Smart IoT - SAT Gateway
gNB & MEC
Remote Controlled AGV
Mixed Reality &
Haptic Gloves
The objective of this use case is to interconnect
varieties of sensors and actuators to a centrali-
sed controller running in a Multi-Access Edge
Computing (MEC) node. The demo will be
carried out using a robotic arm equipped with
a 3D sensor camera and an ASTI Mobile Roboti-
cs Automated Guided Vehicle (AGV). The
robotic arm and the AGV will be synchronized
thanks to the 5G network and will be controlled
by applications that run in the MEC. This AGV is
specially designed for the automotive sector
and is characterized by its simplicity of use,
fexibility of implementation and usefulness in
assembly line automation and internal
transport of materials.
This use case enables centralized,
IoT-based defect monitoring of train
axles. While passenger rail technolo-
gy has progressed rapidly over the
past years, most commercial rail
carriages rely on technology develo-
ped more than 40 years ago. Cost
pressures used to be the driving
argument, but the age of digitization
has changed the equation parame-
ters. Operators must increase
operational availability and reduce
maintenance costs, logistic
operators must plan and perfectly
orchestrate logistic assets, and
customers and consumers want to
know when their orders arrive. This
data driven evolution enables a new
business case.
This use case focuses on enhancing the situatio-
nal understanding of events in maritime ports
and terminals by means of collecting and
aggregating data processing from multiple data
sources like Port Community Systems, M2M
platforms, etc. A subsequent optimization and
prediction performed on this data will reduce
the time that trucks spend inside the port and
terminal facilities, i.e. truck turnaround times.
The outcomes of the monitoring and optimiza-
tion processes will be visualized in a dashboard
and map interface. The use case will be demon-
strated at the ports of Valencia and Livorno.
The use case proposes a centralized
approach for data exchange and manage-
ment between heterogeneous M2M and
DLT solutions, abstracting their complexity
by means of Data Virtualization Layer and
Cross-DLT Layer. It will support data
aggregationandpersonaldatadetectionas
well as pseudonymization in order to meet
the requirements of GDPR, so that different
stakeholders from the maritime domain
can manage and keep track of their own
data sets, benefiting from the security
capabilities provided by heterogeneous
DLTs (i.e. proof-of-existence).
This use case aims at providing tele-opera-
tion driving with mixed reality and haptic
solution to remotely control an AGV for the
aid of the fully automated transport system.
The telepresence is allowed by making use
of an indoor cockpit, cameras and sensors
mounted on the AGV, a low latency 360º
video projected into the virtual reality
glasses and haptic feedback sent to the
operator hands. A 5G RAN is used to provide
uplink and downlink connectivity to all
cameras and sensors installed on the
vehicle and the hosting of MEC applications
for the immersive cockpit.
This use case aims at providing end-to-end
asset tracking via satellite backhaul,
enabling real-time monitoring of predeter-
mined parameters (temperature, humidity,
movement, bumps, etc.) of shipping
containers when they are sailing on the sea,
as well as via terrestrial IoT connectivity
when the ship approaches the port. To
enabletheubiquitouscoverage,IoTtracking
devices will be installed on the shipping
containers transported by ships and trucks
on both segments. Hence, it would allow
supply chain players to achieve operational
excellence and major reductions in
operational uncertainties.
Automated Robots
with Heterogeneous Networks
Supply Chain Ecosystem
Integration
Transportation Platform
Health Monitoring
Situational Understanding
and Predictive Models
in Smart Logistics Scenarios
Improve Drivers’ Safety
with MR and Haptic Solutions
Inter-modal Asset Tracking
via IoT and Satellite