# Autonomous Wireless Sensor Networks in
## 4 Discussion  
In this paper, we described our experimental PentaSense WSN network set-up in a field site in Belgium and output generated by two models related to the climatic suitability for the establishment and meteorological suitability driving the inter-annual dynamics of the mosquito vector _Ae. albopictus_. Thus, we examined the feasibility of integrating an autonomous low-cost wireless sensor network with a spatial decision support system meeting the specific requirement of IPM applications. We designed, executed and analyzed a set of tests evaluating the basic Quality of Service of the WSN. Firstly, the following metrics were considered for the SatCom module: (i) Signal Strength; (ii) Data Loss; (iii) Bandwidth; and (iv) Course Grain Localization. Secondly, for the WSN nodes we performed tests for the following functionalities: (i) Point-to-point communication; (ii) Energy autonomy; (iii) Mesh network configuration; (iv) Automated node discovery; and (v) Data loss. The results showed that the signal strength of the SatCom module was highly dependent on the fraction of the sky obscured by clouds, and for values above 5/10, the signal strength would be low enough to cause data loss which was observed in the number of billed and received data packets. During the test, we discovered several configuration bugs which lead to loss of data due to the SatCom module itself. Our best guess is that this happens when a data packet is received at the server of the service provider, but the CRC shows a malicious receipt. The packet is billed, but not sent to the end-application due to data corruption. This only happens under the condition that the signal strength is below level 3. This type of data loss can be avoided by having the data sent only when the signal strength is 3 or higher. The system performed well regarding the evaluated metrics and met the criteria for IPM deployment. The WSN is suitable for large-scale as well as small-scale applications. The scale of the system will significantly depend on the pest species and type of real-world deployment. For certain mosquito vectors small-scale monitoring with a denser sensor network is important to capture the micro-climatic conditions of the resting habitats; while, for example, for the olive fruit fly (Bactrocera oleae) sensors coupled with automated traps are used on larger spatial scales with a less dense network to monitor the population across the orchards which can span from 100-500 trees for small orchards in Turkey to 2000-5000 trees for big orchards which are typical for Spain and Australia. The system has a high degree of modularity in terms of the spatial scale of deployment due to the global coverage of the Iridium SBD module as well as high availability of public LoRa providers, with LoRaWAN being the leading open global standard for secure LPWAN connectivity and wide range communication. For small inter-node distances of up to 50 m, the nodes communicate with RF while for greater distances the system uses LoRa communication, while the traffic load and number of nodes in our application was small. The total network yield for standard IPM applications (up to 30 nodes per ha) is still relatively low and will not impact data loss due to delivery or end-to-end delay. The outputs of the suitability model for _Ae. albopictus_ are in accordance with previously published work [45; 46; 47] indicating that Belgium is suitable for the establishment of the invasive vector species. _Ae. albopictus_ has last been detected in 2016 [48] and previously in 2013 and 2014 [49]. The mosquito is still not established in Belgium, however, is crossing the border from neighboring countries such as Germany and France. The spread needs to be closely monitored to prevent the mosquito from gaining a foothold in Belgium. Models supported by WSN data can guide surveillance and monitoring efforts on a country level.