Emergency response during mission critical scenarios are very important to saving lives. Even though there exist systems for risk calculation and mitigation there is also a need to evolve current state of art for such systems that mitigate risk by analyzing IoT data including fusing human-based data with sensor data. In such systems, measurements are not only taken by calibrated hardware sensors, but also humans, who contribute their subjective ‘measurements’ such as their individual sensations, current perceptions and personal observations to risk calculation.

As an example of a domain that could benefit from fusion of human and hardware sensor data are systems for vehicle accident prevention and response. Vehicle accidents are a major concern, since they not only endanger the wellbeing of human occupants of these vehicles, but may also threaten non-road users (e.g. nearby pedestrians). This is true even for vehicles with autonomous driving functionality.

On one hand, there exist reactive systems that mitigate the risk of fatal or grievous injuries, given that the accident is unavoidable. Such systems involve on-board vehicle sensors and hardware such as airbags and crumple zones. On the other hand, there exist proactive systems that try to prevent an accident from happening to the extent possible. Such systems also include some type of sensor hardware combined with actuation of one or more vehicle control functions, such as emergency braking and steering.

Such systems can benefit from fusing sensor-data measuring vehicle dynamics, with data measuring condition of the driver, occupant and pedestrian data (for example, level of tiredness, intoxication, their pattern of driving, emotions, etc.).

Beyond risk assessment for a particular vehicle, cellular technologies such as LTE and next-generation 5G are important in assessing risk for groups of vehicles, for example making use of an “off-board” function installed in base stations. Additionally, there exist systems for notifying other vehicles in proximity about the calculated risk of an accident occurring using cellular technologies and neighboring base stations.

There are several different other use-cases possible such as Air-traffic control and medical emergency response. In each of such cases, some technology options are already available to a certain level, but, some people argue that these are not sufficient to help support these essential needs.

This session will carefully consider these arguments and the different solutions that are available. Focus will be given to finding the right technology mix to ensure not only technical feasibility, but also societal acceptance and commercial/business viability. This includes discussions around IoT, 5G and Machine Learning - seen by many as the industry’s key enablers.

This workshop would initially explore the requirements of such systems, review current research and offer an opportunity for academic and industrial research collaboration to discuss and evolve feasible architectures including such ecosystems, IoT, 5G and machine learning for the pragmatic realization.


The technical topics of interest include, but are not limited to:

· Existing and future IoT based emergency response standards, architectures and technologies
· Existing and future use cases and deployment of large IoT systems in mission critical scenarios using LTE or 5G networks
· Design and evaluation of large IoT test beds, prototypes, and platforms for mission critical IoT application development and deployment
· Usecases and design of mission critical systems using fusion of human and hardware sensor data
· Machine Learning in IoT context for mission-critical scenarios
· Game-theoretic and Artificial Intelligence mechanisms for IoT resource allocation and management
· Integrating 4G and 5G wireless technologies into IoT communications and platforms
· Integration of cognitive technologieswith mission critical IoT systems
· Energy-efficient communications considering opportunistic policies for large mission critical IoT systems
· Big data and data analytics solutions for mission critical IoT systems
· Comparison and improvement of mission-critical IoT communication protocols
· Novel, distributed technologies for addressing mission-criticality in cellular network infrastructure (e.g., Edge/Fog computing, Quality of Service)