Being the main pillar in the context of Industry 4.0, the Internet of Things (IoT) leads evolution towards a smarter and safer planet. Being human-centered, rather than machine-centered, as was the case of wireless sensor networks used in the industry for decades, the IoT may enhance human intelligence with situational awareness, early warning, and decision support tools. Focusing on air cargo transportation, the “INTELLICONT” project presented a novel solution capable of improving critical air cargo challenges such as the reduction of total aircraft weight, detection and suppression of smoke and/or fire in a container, elimination of permanent moving and locking hardware, loading and unloading logistics enhancement and maintenance. In the present work, the IoT-based monitoring and control system for intelligent aircraft cargo containers is presented from a hardware perspective. The system is based on low-cost, low-energy sensors that are integrated into the container, can track its status, and detect critical events, such as fire/smoke, impact, and accidental misuse. The focus has been given to the design and development of a system capable of providing better and safer control of the aircraft cargo during the loading/unloading operations and the flight. It is shown that the system could provide a breakthrough in the state of the art of current cargo container technology and aircraft cargo operations.

Based on the constant need for safety and operational cost optimization, the air-cargo industry is continually evolving in the context of Industry 4.0. Used wisely, data can help the industry to provide critical resilience that will allow authorities to take proper measures/actions in response to unexpected disasters and secure societal protection. The “INTELLICONT” project combines state-of-the-art technologies blended with novel solutions to improve the loading/unloading time, the structural status awareness, and the safety and security of the air-cargo related operations (prior to, during, and after the flight), as well as to enhance their capabilities related to the execution of their duties. The suggested system is contextually aligned and harmonized with the existing international and EU regulations. In the present work, the remote monitoring and control system for intelligent aircraft cargo containers have been presented from the software perspective. The intelligent containers integrate three types of sensors, Structural Health Monitoring, fire suppression, and locking status indication. The focus has been given to the design and development of a Human Machine Interface (HMI) capable to visualize all related data for better and safer control of the aircraft cargo. It is shown that the system can contribute to making the air transportations safer, environmentally friendlier, faster and with the lowest possible cost.

In response to mounting regulatory and environmental pressures, the maritime sector must urgently improve energy efficiency and reduce greenhouse gas emissions. However, conventional operational interfaces often fail to deliver real-time, actionable insights needed for informed decision-making onboard. This work presents an innovative Augmented Reality (AR) interface integrated with an established shipboard data collection system to enhance real-time monitoring and operational decision-making on commercial vessels. The baseline data acquisition infrastructure is currently installed on over 800 vessels across various ship types, providing a robust foundation for this development. To validate the AR interface’s feasibility and performance, a field trial was conducted on a representative dry bulk carrier. Through hands-free AR smart glasses, crew members access real-time overlays of key performance indicators, such as fuel consumption, engine status, emissions levels, and energy load balancing, directly within their field of view. Field evaluations and scenario-based workshops demonstrate significant gains in energy efficiency (up to 28% faster decision-making), predictive maintenance accuracy, and emissions awareness. The system addresses human–machine interaction challenges in high-pressure maritime settings, bridging the gap between complex sensor data and crew responsiveness. By contextualizing IoT data within the physical environment, the AR-IoT platform transforms traditional workflows into proactive, data-driven practices. This study contributes to the emerging paradigm of digitally enabled sustainable operations and offers practical insights for scaling AR-IoT solutions across global fleets. Findings suggest that such convergence of AR and IoT not only enhances vessel performance but also accelerates compliance with decarbonization targets set by the International Maritime Organization (IMO).

The authors would like to make the following corrections about the published paper