## 4 Evolution towards Greater Complexity  
Research on emergency evacuation systems has evolved from the simpler to the more complex, starting with homogeneous systems, which evacuate people with the help of a distributed WSN. This type of system emphasises in-network intelligence to find safe evacuation paths based on sensing data. Then, we have moved toward a heterogeneous emergency evacuation system which separates functionalities into a distributed decision system and a sensing system to overcome the limitations of a homogeneous system. The sensing system will report multi-domain sensing information from mobile user clients and sensing clients to the distributed decision system so as to facilitate the interaction among the cyber and physical worlds. The third approach takes advantage of parallel agents to achieve fast-than-real-time prediction and discover deep knowledge. The fourth emerging approach relies on Grid computing technologies to find out contextual information for decision makers and handle a huge amount of data to predict dynamic hazard in a parallel way. Finally, by introducing intentional mobility to emergency response systems, mobile entities are exploited to design more flexible and complex search and rescue systems. Based on this evolution, we will discuss the issues on communications, information acquisition and dissemination, knowledge discovery, heterogeneous system integration and asynchronous control. As the system becomes more complex, it can provide more precise prediction and decision, deeper knowledge, large-scale emergency support, and richer emergency response and bring better scalability, flexibility, system lifetime, and fault-tolerance. However, a more complex system relies on much more prior knowledge and complex technologies which will involve hardware costs and overheads in terms of network integration, cross-network communications, cross-machine computation, data management, networking infrastructure, distributed system management, integration control among diverse entities, resource management, and deployment. As different approaches aim at different objectives, open problems are still stimulating new research activities in emergency evacuation and rescue systems. For a WSN-based emergency evacuation system, if nodes break down or are moved by the hazards, system resilience and quality of information [52] are of concern. In addition, while most existing studies aim at an indoor system, an emergency evacuation system for outdoor and underground environments are also needed. Since decentralised evacuation systems improve network lifetime and scalability by separating the sensing system and decision system but new network security risks such as Denial of Service also emerge [53]. Opportunistic networks (OppNets), opportunistic sensing (OppSense), inter-device security, and collaborative intelligence stimulate novel communication and computing paradigms. As contact duration among devices is limited (_i.e._, limited bandwidth) and sensing data is collected intermittently, it is of interest to exploit the limited bandwidth to exchange information with the highest knowledge reward [54], assure security of information exchanges, and discover knowledge behind short-lived and intermittent data to enhance system intelligence in a self-contained way are challenging problems. While agent-based simulators offer the capability to discover deep knowledge from learning [55] and behind collected data, human behavior modelling, augmented reality [56], activity analysis and inference, and social behavior in emergencies can be considered to enhance system intelligence. AsGrid or cloud supported systems can improve the system scalability, managing big data (a huge amount of data) is inevitable, and data analysis technologies will need to incorporate multi-domain information (for example, localization technologies may consider low-accuracy WiFi/GSM information to compensate for the lack of high-accuracy GPS).