# Design and Evaluation of IoT-Enabled Instrumentation for a Soil-Bentonite Slurry Trench Cutoff Wall
## 8 Conclusions and Future Work  
In this project we successfully connected an industrial datalogger to a modern data storage and web-based visualization pipeline to achieve our goals of high reliability and the timely presentation of remote site data in a format facilitating analysis of the data. Throughout this process we relied heavily on open-source software and systems and released our own point-to-point reliable data transport protocol as open-source. This project can be used as a model giving credibility and validation to support other projects adapting other legacy scientific instrumentation onto the internet of things.  
We conclude that this system can be used in the context of on-demand slurry trench cutoff wall structural health monitoring system for real-time stress detection linked to hydraulic conductivity. For on-demand monitoring of slurry trench cutoff wall projects in homogeneous soil conditions, the number of sensor cages could be reduced from four to one located near the bottom of the trench. This one instrumentation cluster coupled with one set of inclinometers and piezometers located at the same station as the instrumentation cluster would provide real-time monitoring of stresses which are directly linked to changes in hydraulic conductivity. This in situ measurement approach is a significant improvement over current quality control measures that are predominantly ex-situ.  
In the future, we would like to generalize this approach to make it easier to apply to new projects. The currently deployed system has software that runs (1) at the site, (2) on the gateway, and (3) on the server. Each of these currently needs to be manually installed and configured for the whole system to operate. The software running on the Raspberry Pi at the site could be provided as a complete system image file that could be used to download from any compatible datalogger. The gateway software could be provided in a similar manner. However, because the web interface was developed specifically for this project, for each new project a new web interface would have to be manually created. However, the datalogger has sufficient metadata to automate this process. Our long-term vision is a plug-and-play solution to collecting, transporting, storing, and visualizing data from any supported datalogger.  
Conceptualization, J.E. and A.M.; methodology, J.E. and A.M.; software, Y.L. and A.M.; validation, J.E. and A.M.; formal analysis, A.M.; investigation, J.E. and A.M.; resources, J.E.; data curation, A.M.; writing--original draft preparation, J.E. and A.M.; writing--review and editing, J.E. and A.M.; visualization, A.M.; supervision, J.E. and A.M.; project administration, J.E.; funding acquisition, J.E.  
This research was funding by the National Science Foundation under award number 1463198.  
Figure 12: Radio performance measurements from the site from September 2018.  
**Acknowledgments:** The authors would also like to acknowledge the contributions of CETCO which donated the bentonite for this project, Central Builders Supply which provided on-site support during construction and the study location, and Geo-Solutions, Inc. which performed the construction. The project would not have been possible without the support of these companies. In addition, the authors acknowledge the Jeffrey C Evans Geotechnical Engineering Laboratory endowment, established through the generosity of [PERSON] and [PERSON], which was used to provide financial support for the students and faculty. Special thanks are also given to [PERSON], Director of Bucknell University's Civil Engineering Laboratories, for his numerous contributions to this project.  
**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results