# Enhanced IoT-Based End-To-End Emergency and Disaster Relief System
## 2 Related Works  
When conducting disaster relief operations, two relevant challenges arise: (i) setting up an immediate emergency wireless network to inter-connect on-the-field rescuers with trapped survivors; and (ii) relaying the emergency network to the Internet and extended networks. [PERSON] et al. in [10] classify the applications into three main classes: (i) remote health and fitness monitoring, (ii) military and training and (iii) intelligent biosensors for vehicle area networks. Moreover, the authors in [10] discuss a list of research projects and implementations, in particular the Advanced Health and Disaster Aid Network (AID-N) [11], which targets disaster and public safety applications. AID-N uses a wired connection for BAN communication and mesh and ZigBee for the Body-to-Body Network (BBN). Off-body communication in AID-N is fulfilled through WiFi, cellular networks and the Internet. AID-N aims to sense pulse, blood pressure, temperature and ECG. [PERSON] et al. in [12] focus more on the following major medical applications: (i) telemedicine and remote patient monitoring, (ii) rehabilitation and therapy, (iii) biofeedback and (iv) ambient assisted living. The latter work discusses also the QoS requirements for the medical context. Recently, research trends have aimed at relying on large-scale LTE/4G-enabled networks to inter-connect deployed devices during disaster relief operations. For instance, the authors in [13] introduced the Device-to-Device (D2D) communication scheme to allow user equipment (UE) to communicate within the reachable neighborhood. The proposed scheme sets up an ad hoc wireless network, which relies on the base stations evolved NodeBs (eNBs) at the network startup. Therefore, the solution still depends on the 4G network infrastructure. Definitely, the unavailability of the 4G backbone causes the unavailability of the proposed D2D wireless network. We cite among, other works, approaches that studied and implemented alert messaging systems, such as the Reliable Routing Technique (RRT) [14] and TeamPhone [15]. Both approaches consist of setting up a smartphone messaging system, which is able to send alert notifications by bridging cellular networks or over ad hoc and opportunistic networks. These proposed systems seem to solve the connectivity issues on-the-field between rescuers and trapped survivors. However, devices in the disaster area may only communicate within one hop. Devices select one next hop only, and no neighborhood discovery is done. Thus, RRT and TeamPhone are not topology-aware and do not consider external network extension with the Internet or other networks. The authors in [16] propose a localization-based and network congestion adaptive approach called \"DistressNet\". DistressNet is claimed to be efficient in congestion avoidance during disaster relief operations; however, this approach is not appropriate for indoor rescue operations due to its localization mechanism, which renders multi-hop algorithms inefficient. The authors in [17] adopted the WiFi Direct standard for the \"Emergency Direct Mobile App\", which is intended to divide the set of smart phones into groups communicating in peer-to-peer mode assured by WiFi Direct. One of the devices is selected as the Group Owner (GO) and acts as the access point for its group and as a gateway elsewhere. The rest of the devices act as Group Relays (GR). The network topology formation in this strategy causes an important delay. Additionally, with regards to the high mobility imposed by the emergency context, the network topology update (i.e., GO negotiation and election, GR selection) increases data transmissions latency. The earliest proposed schemes aim to enhance the on-body devices' transmission reliability and to improve the energy efficiency. [PERSON] et al. in [18] proposed a novel Cross-Layer Design Optimization (CLDO) scheme. Indeed, the design of CLDO relies on the three lower layers (i.e., PHY, MAC and network layer). Power consumption is firstly optimized by selecting optimal power relays.