Abstract

SensIoT is an open-source sensor monitoring framework for the Internet of Things, which utilizes proven technologies to enable easy deployment and maintenance while staying flexible and scalable. It closes the gap between highly specialized and, therefore, inflexible sensor monitoring solutions, which are only adjusted to a specific context, and the development of every other solution from scratch. Our framework fits a variety of use cases by providing an easy to set up, extensible, and affordable solution. The development is based on our former published framework MonTreAL, whose goal is to offer an environmental monitoring solution for libraries to guarantee cultural heritage to be conserved and prevented from serious damage, for example, from mold formation in closed stocks. It is a solution with virtualized microservices delivered by a famous container technology called Docker that is solely executable on one or more single board computers like the Raspberry Pi by providing automatic scaling and resilience of all sensor services. For SensIoT we extended the capability of MonTreAL to integrate commodity servers into the cluster to enhance the ease of setup and maintainability on already existing infrastructures. Therefore, we followed the paradigm to distribute microservices on small computing nodes first, thus not utilizing well-known cloud computing concepts. To achieve resilience and fault tolerance we also based our system on a microservice architecture, where the service orchestration is solved by Docker Swarm. As proof of concept, we are able to present our current data collection of the University of Bamberg’s Library that runs our system since autumn 2017. To make our system even better we are working on the integration of other sensor types and better performance management of SD-cards in Raspberry Pis.

Highlights

  • In the last couple of years, advancements in Internet technologies, which enabled networking of everyday objects, significantly increased the popularity of the Internet of Things (IoT)

  • The principles of SensIoT are the same as the ones of MonTreAL: SensIoT operates with an arbitrary number of small sensor devices like the Raspberry Pi (RPi) which can be equipped with sensors to collect environmental information

  • Since SensIoT evolved from MonTreAL, its original focus laid on working with temperature and humidity sensors and, SensIoT sensor devices can currently be equipped with remote ASH2200 sensors through USB utilizing a USB-WDE-1 receiver and low-cost DHT11, DHT22, and AM2302 sensors through GPIO

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Summary

Introduction

In the last couple of years, advancements in Internet technologies, which enabled networking of everyday objects, significantly increased the popularity of the Internet of Things (IoT). Like MonTreAL [2], SensIoT is based on the work of Lewis et al [3], which proposes an environmental monitoring solution in a quality-controlled calibration laboratory They used the RPi 1 with the Raspbian operating system (OS) in Wireless Communications and Mobile Computing their architecture while their sensor interfacing is written in the Python programming language. The components were sealed within an acrylic case and placed in coastal areas to measure water dynamics and gather data about the seafloor In contrast to those approaches, which mostly cover small application areas with very specific conditions and cloud connectivity, the further development of MonTreAL focuses more on being a general sensor monitoring framework fitting more use cases by being extensible and applicable. There is currently no general sensor monitoring framework similar to SensIoT available and besides MonTreAL none of them makes use of container virtualization to simplify the overall deployment and maintenance of their application

Foundations of SensIoT
Container Virtualization for Use Cases of the Internet of Things
Architectural Modularity of SensIoT
Dataflow of SensIoT’s Modules
Data Acquisition by the Sensor’s Module
Data Transmission by a Messaging Queue
Data Persistence by Databases
Data Visualization through Dashboards
Comparison
10. Accessing SensIoT through Its Web API
11. Extensibility of SensIoT
12. Performance Evaluation on a Raspberry Pi Cluster
13. Stress Testing of SensIoT
14. Conclusion
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