# An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors
## 4 Experimental Setup and Node Architecture
### Deployment (II)  
The second deployment was carried out as a part of a research activity in smart monitoring of beehives [9]. The main goal of this research is to obtain knowledge of the conditions within the hive, and use this knowledge to inform the beekeeper, with the aim of maintaining a healthy hive through the use of heterogeneous WSN and mobile technologies [9]. The same deployment is also used for weather prediction [9].  
A deployment period of 14 days has been used in this paper to evaluate the benefits of the proposed approach. The critical parameters that may indicate the status of the beehive were identified as: temperature, humidity, Carbon Dioxide (CO\({}_{2}\)) levels, and Oxygen (O\({}_{2}\)) levels [32; 33]. These are known to vary in response to one or more of these scenarios: the number of honeybees in the hive, the health of the colony, and the external weather conditions [9].  
As the proposed approach aims to reduce the power consumption of the power hungry sensors, the data collected with the CO\({}_{2}\) sensor (as the most power hungry sensor) were selected for focus over the 14 days of the deployment. This means that the EASA was performed on the CO\({}_{2}\) data as being one of the most important gas sensors in the hive that would give the most significant information about the beehive condition. The platform used for deployment (II) is an off the shelf WSN platform, Libelium \"Waspmote\" v1.2. It is a low power platform based on Atmega microcontroller, with a modular architecture allowing a combination of over 70 sensors and 11 radio technologies, with a built in SD card slot and an accelerometer. The gas sensors selected for the actual deployment were off the shelf CO\({}_{2}\) and O\({}_{2}\) gas sensors that could be interfaced with the gas sensor board developed by Libelium. Additionally, an NO\({}_{2}\) sensor and two air contaminants sensors were deployed. The actual sensors used in the deployment are: molecular oxygen (O\({}_{2}\)) SK-25; carbon dioxide (CO\({}_{2}\)) TGS4161; nitrogen dioxide (NO\({}_{2}\)) MiCS-2710; and two air contaminants TGS2600 and TGS2602, which sense gases including ethanol (CH\({}_{3}\)CH\({}_{2}\)OH), hydrogen sulfide (H\({}_{2}\)S), and methane (CH\({}_{4}\)). The base station used for this deployment was a bridge between the ZigBee network and the 3G network. It used an XBee Series 2 ZigBee radio and a GSM/GPRS/3G module to send the data to a server. The main issue that was encountered in this deployment was the long sampling period of each of the four sensors and hence very high energy consumption of the system during the sampling state. The results of this deployment have shown that even using an energy harvesting source (_i.e._, solar) does not guarantee a long lasting WSN node. For this reason, these deployments will benefit significantly from the adaptive sampling using the EASA. The five sensors and the battery in deployment (II) were sampled every 4 h, which translates to a sampling rate of 0.000069 Hz (or 1 sample every 14,400 s).