# Composing as a Service: A Real-World IoT Implementation
## 4 Field Evaluation
### Evaluation  
The evaluation of composting systems is a rather long procedure and requires deep expertise in the field. To evaluate the efficiency of the proposed architecture, we implemented a completely supervised composting procedure and the unsupervised composting procedure provided by the presented system, and compared the produced results. In more detail, approximately 20 m\({}^{3}\) of household-produced organic waste was disposed of in a designated field to undergo composting. The whole procedure was continuously supervised by experts to guarantee the optimal development of the composting process. In several cases, the experts performed actions such as watering or drying the compost material to meet the appropriate conditions in humidity and temperature, allowing the process to progress uninterrupted. Similarly, approximately 20 m\({}^{3}\) of the same material was disposed of in the presented composting frame. The whole procedure was performed in a completely unsupervised manner. Both procedures produced high-quality compost and performed as expected. The total duration of the manual procedure was three months, and required the employment of two experts for the overall supervision of the process. The presented system took two months to complete and required no supervision at all. The produced outcomes from both processes were rather similar in quality and quantity.  
Figure 10: Real-time sensor data.  
The evaluation of composoting systems is a rather long procedure and requires deep expertise in the field. To evaluate the efficiency of the proposed architecture, we implemented a completely supervised composoting procedure and the unsupervised composoting procedure provided by the presented system and compared the produced results. In more detail, approximately 20 m\({}^{3}\) of household-produced organic waste, were disposed in a designated field to undergo the composoting procedure. The whole procedure was continuously supervised by experts, to guarantee the optimal development of the composoting process. In several cases, the experts performed actions such as watering or drying the compost material to meet the appropriate conditions in humidity and temperature, allowing the process to progress uninterrupted. Similarly, approximately 20 m\({}^{3}\) of the same material was disposed in the presented composoting frame. The whole procedure was performed in a completely unsupervised manner. Both procedures produced high quality compost and performed as expected. The total duration of the manual procedure was three (3) months and required the employment of two experts for the overall supervision of the process. The presented system took two (2) months to complete and required no supervision at all. The produced outcomes from both processes, were rather similar in quality and quantity.  
Figure 11: System settings.  
With respect to the IT infrastructure we used and the overall evaluation of the system we developed, the following can be highlighted:  
* Our IoT gateway runs on Raspberry Pi 3 model B+ equipment without any performance issues. Taking into consideration that data processing at the edge is limited, it is obvious why there is no requirement for more processing power at this layer.
* Our cloud infrastructure is hosted on a virtual machine with 2 dual-core CPUs and 8 GB RAM. These hardware resources are enough for our deployment that includes only one composting frame. However, considering the operation of data aggregation and analysis using neural networks, which takes place on the Cloud, potential scaling of the system to include more composting frames definitely requires more resources. With respect to data storage, our system consumes almost 50 GB of hard disk for every reporting two-month reporting period.
* The communication delay between the IoT gateway and the cloud application does not exceed 10 ms. Our gateway is wired, connected to the Internet through a gigabit Ethernet connection.