# The Design and Deployment of an End-To-End IoT Infrastructure for the Natural Environment
## 3 Related Work  
As mentioned in the introduction, the vast majority of Internet of Things research to date has been focused on smart city and home environments [13]. The instrumentation of the natural environment using IoT technology has received less attention. The key practical differences here are the lack of wide-area connectivity, lack of mains power sources, physical locations that are hard to access, and the often harsh environmental conditions. We survey the most closely related work in this area below. Our deployment is the first to deliver a holistic IoT solution for the natural environment, enabling a real-time study of multiple dimensions of that environment simultaneously. One of the first experimental testbeds of a multi-tiered architecture for habitat monitoring was proposed by [PERSON] et al. [14] in 2001. Using the more technology developed by [PERSON] at the University of California, Berkeley [15], the authors introduced the principles of building long-lived wireless sensor networks, adaptive self-configuration, and its application to habitat monitoring. Their goal was to integrate these building blocks into a deployable system. Researchers at UC Berkeley in collaboration with biologists at the College of the Atlantic deployed the first-documented tiered wireless sensor network architecture for habitat monitoring, such as detecting the presence of birds on Great Duck Island (GDI), Maine [16]. They deployed two networks for a total number of about 150 nodes in both single-hop and multi-hop configurations. The initial deployment comprised of 32 nodes using UC Berkeley motes, including temperature, photoresistor, barometric pressure, humidity, and infrared sensors. Two years later, the researchers analysed a rich set of data captured from these sensors from a systems perspective regarding the lifetime of nodes and network performance, reliability, routing, and yield [17]. Researchers from Princeton University deployed a 30-node wireless sensor network with mobile base stations called ZebraNet at the Mpala Research Center in central Kenya which aimed at monitoring and tracking wildlife, particularly zebras, for biology researchers [18]. The ZebraNet system included nodes (tracking collars carried by animals) operating as a peer-to-peer network for transferring data. The collar, working as a wireless computing device, was comprised of a GPS, flash memory, a wireless transceiver, and a CPU. ZebraNet was the first project to design protocols for sensor networks having a mobile base station. The University of California, Los Angeles's (UCLA) Center for Embedded Network Sensing (CENS) deployed the Extensible Sensing System (ESS) for habitat sensing at the James Reserve in California. CENS was a multidisciplinary collaborative project to develop and deploy wireless sensing systems to monitor the biological, ecological, seismological, and different environmental phenomena. Researchers at the University of Southampton deployed an environmental sensor network called GlacsWeb [19] to monitor and study the dynamics of glaciers in hostile environments. The system comprised of 9 nodes (probes) inserted in the glacier, a Base Station on the surface of the glacier having a differential GPS, and a Reference Station working as a gateway for transferring data. Each node was equipped with pressure, temperature, and orientation (tilt) sensors for monitoring the melting behaviour of glaciers. GlacsWeb developed a low-power sensor network supporting the transfer of sensor readings to a web accessible database. [PERSON] et al. [20] designed and implemented a reactive, event-driven wireless sensor network for the environmental monitoring of soil moisture. A novelty of their implementation is how their network reacts to extreme events such as intensive rainfall to send frequent readings and to collect the most interesting data, reverting to a less frequent collection in periods of lower rainfall.