# A Social Environmental Sensor Network Integrated within a Web GIS Platform
## 2 Related Work
The environmental conditions were analyzed through specific software operating on every system component and presented real-time and total recordings in a GUI. The methodology of water monitoring allows to avoid fish mortality and could be applied in various fields of environmental sensing. The adherence of proper hygiene practices in public health institutions is a subject studied by [PERSON] and [PERSON] [25] through the implementation of IoT and WSN technologies. Their prototype system aims at monitoring hand hygiene compliance rates through cloud-connected monitoring stations to monitor hand hygiene events in real-time and in large scale. The proposed platform is consisted by a network of \"smart hand washing\" nodes, which are embedded in a wireless domain through Zigbee communication protocol and UHF-RFID modules. The nodes are divided into Soap Dispenser and Faucet categories that both integrate embedded microprocessors, various sensors and actuators. The automatic soap dispenser, based on Arduino PRO-mini, initiates the hygiene sequence once it is actuated by the user and it is followed by the faucet, based on Raspberry Pi 3, which finalizes the hygiene activity. Networking is based on wireless local area network that establishes communication among nodes and cloud services (Database and Clients) where lower and higher level programming languages have employed on the purpose to measure compliance while counting hand-hygiene occurrences and their total duration. [PERSON] and [PERSON] proposed a novel approach on public health related human actuated events, outwit the scope of environmental sensing and outdoor monitoring. The survey of [PERSON] et al. [26] dealt with applications of WSN to Structural Health Monitoring (SHM) which is referred to the monitoring of critical infrastructures in order to expand their lifespan through \"early damage detection\". This application requires the deployment of numerous sensors throughout a structure for damage localization. Applied WSN for SHM are based on the selection of sensor and sensed parameters--mainly focused on structure's acceleration and velocity through piezoelectric accelerometers. SHM requires the management of a large amount of data with dense population of sensor nodes. Delay in sampling rate depends on the prospect of the monitoring procedure, e.g., long-term allows long delays. Network scalability is highlighted as an important factor in meeting each SHM application quality due to the required \"sheer quantity of data collection and transmission\" and is related to the maximum network node time-synchronization step. Network architecture is improved through hierarchical relationship between a base station and several sensor nodes. Synchronization among the nodes and the base station is implemented by specialized algorithms that are dependent to Time Synchronization Error (TSE) factor. Furthermore, optimal placing of sensor nodes originate from civil engineering perspective and determines the effectiveness of structural information collection. Relatively to scalability, placement is related to network's lifespan, overall connectivity, robustness and decision regarding the implemented routing protocol. Energy efficiency determines network lifespan and affects system operation. Clustering is highlighted as a common technique to improve scalability, simplify routing, extend network lifespan and conserve bandwidth. In addition to the aforementioned, an SHM is capable of carrying several features such as Mobile Phone Sensing (MPS) that extends the system to the capabilities of smartphones (e.g., GPS, accelerometers, cameras etc). WSN consist an effective tool with SHM applications that requires extensive research prior deployment. The common ground between environmental monitoring and SHM is found on sensor locality, network architecture and communication protocols. System intelligence in supply chain is provided by the integration among RFID and WSN. [PERSON] et al.