Thinger.io: An Open Source Platform for Deploying Data Fusion Applications in IoT Environments

Abstract

In the last two decades, data and information fusion has experienced significant development due mainly to advances in sensor technology. The sensors provide a continuous flow of data about the environment in which they are deployed, which is received and processed to build a dynamic estimation of the situation. With current technology, it is relatively simple to deploy a set of sensors in a specific geographic area, in order to have highly sensorized spaces. However, to be able to fusion and process the information coming from the data sources of a highly sensorized space, it is necessary to solve certain problems inherent to this type of technology. The challenge is analogous to what we can find in the field of the Internet of Things (IoT). IoT technology is characterized by providing the infrastructure capacity to capture, store, and process a huge amount of heterogeneous sensor data (in most cases, from different manufacturers), in the same way that it occurs in data fusion applications. This work is not simple, mainly due to the fact that there is no standardization of the technologies involved (especially within the communication protocols used by the connectable sensors). The solutions that we can find today are proprietary solutions that imply an important dependence and a high cost. The aim of this paper is to present a new open source platform with capabilities for the collection, management and analysis of a huge amount of heterogeneous sensor data. In addition, this platform allows the use of hardware-agnostic in a highly scalable and cost-effective manner. This platform is called Thinger.io. One of the main characteristics of Thinger.io is the ability to model sensorized environments through a high level language that allows a simple and easy implementation of data fusion applications, as we will show in this paper.

A Systematic Review of IoT Solutions for Smart Farming

“…Sensor nodes, for example, are used to monitor plant diseases [ 26 ], control environmental variables in greenhouses [ 27 ] and external crops [ 28 , 29 , 30 ], among others. The interaction between the devices that belong to the perception layer and the services that belongs to the processing layer is intermediated by the transport layer and might occur in several ways, such as through the direct communication between sensor nodes and a data processing platform (such as FIWARE [ 31 ], SmartFarmNet [ 32 ] and Thinger.io [ 33 ]) or through a gateway that, besides intermediating the communication between sensor nodes and the internet, acts as a data hub and enables the communication between network protocols that are originally incompatible, such as ZigBee and the Internet [ 28 ].…”

Analysis, Deployment and Integration of Platforms for Fog Computing

“…Thinger.io [9] is an open source IoT platform that follows the cloud computing model, providing communication with system nodes, storage and data visualization, among other features. It places special emphasis on efficient data transmission, real-time two-way communication, interoperability, and deployment simplicity.…”

Rancang Bangun Alat Prototipe Pendeteksi Kebakaran dengan Android Melalui Internet of Things

“…Untuk merealisasikan sistem dengan konsep internet-of-things, platform standar berbasis open source sudah banyak dikembangkan misalnya Cayenne (Das dan Mahata, 2019), Blynk (Serikul dkk., 2018;Media's dkk., 2018), ThinkSpeak (Al-Omary et al, 2019), DeviceHive (Lyaskov et al, 2017), Thinger.io (Bustamante et al 2019), dan sebagainya. Dalam makalah ini, prototipe yang dibangun menggunakan platform Blynk untuk merealisasikan internet-of-things-nya.…”