As we mentioned in the previous post, Sofia2 IoT Platform has promoted the development of high added value solutions in customers in areas such as Smart Cities, Smart Health, Industry, Retail, Energy …
One of the projects which Sofia2 serves as a technological base is eVacuate, a European innovation project whose aim is the development of a simulation and emergency management system based on IoT and Big Data technologies to define in real time the optimal routes of evacuation in large infrastructures.
During the last months four pilots have been carried out in which the feasibility of the project has been demonstrated and the possibility of scaling in a great number of scenarios.
The first evacuation exercise was held last October at Anoeta football stadium. 27 researchers from different European companies and universities were working in San Sebastián defining in real time the optimal evacuation routes for a football match in Anoeta. To do this, a good number of fans were gathered and they were asked to be placed in the main tribune. From that moment, they followed workers instructions and they lived in situ up to four types of different evacuation situations. The announcements of public address, signage, opening of doors and emergency situations varied with the aim of creating four completely different cases.
Here you have the video with the images and all the detailed information of the pilot in Anoeta.
Athens airport, a cruise ship of the company STX on French coast and finally, last May, Bilbao’s Subway, were the other scenarios in which eVacuate demonstrated its effectiveness. In all cases it was possible to reduce the evacuation time by more than 25% compared to the current evacuation systems.
Release 4.1 of Sofia2 IoT Platform is already available.
In this release has been made available the Sofia2 CloudLab Experimentation Platform
See other releases
This release has been centered on improving and incorporating new tools for the developer, among them we can highlight:
IMPROVEMENTS IN THE CONTROL PANEL
Inside the value proposal for the Sofia2 platform, the developer is a key element, and in this line we are continuously working on improving the relationship of the developer with the console:
- New control panel landing page: From now on when a user accesses the console is presented with a graph displaying his ‘Sofia Universe’, that is, created entities (ontologies), clients (ThinKPs), dashboards, rules… and their relationships. Also, clicking on each of this elements you can navigate straight to their specific UI.
- Console integrated help: From now one you can search for any term directly from the console, for example, this search is done over the blog:
and over the platform web help:
AND NEW UTILIDES FOR THE USER OF THE PLATFORM:
Also, following the line of simplifying the platform user’s daily life, we have incorporated new tool we hope can ease their day-to-day:
- Exportation and importation of elements between environments: This functionality allows, from the control panel, to select the elements created in an environment (ontologies, projects, ThinKPs, APIs) and export them. The platform generates a ZIP file able to be used later for import on another platform. With this mechanism I can start development on one environment and later migrate everything to another in a simple way.
- Sofia2 project integration with Git: The platform allows to configure a connection with a git repository. Once this is configured by an administrator, when we create a project, this will replicate the structure in the Git repository.
- Ontology to Java DTOs: This allows to generate a Java class from an ontology (including annotations to migrate from Java to Json and viceversa).
- Improvements on the scripting engine: To help with the script creation, the editor now supports autocompletion (using to Ctrl+Space combination).
Also on the process log the script errors can be found:
NEW FUNCTIONALITIES ON THE DASHBOARD ENGINE
Bases on the requirements identified on some projects we collaborate with we have also included:
- Parameter passing either to gadgets or dashboards, so they can, in turn, pass them to the queries they use to load data
- ·Text internationalization: From the editor we can now define an internationalization JSON to be used on the fields:
- Gadget templates: This functionality allows to make available a HTML5 as a template so other users can create their own gadgets completing the template with their own parameters associated to the gadget.
- Weather type gadget : Depending on the configuration now it is possible to display temperature and predictions based on location
NEW FUNCTIONALITIES ON THE SYNOPTIC ENGINE
This module started as a demonstration on what could we do with the platform and SVG web technologies on a field traditionally dominated by the SCADAs.
Thanks to the improvements identified by the collaborators, on this new version we support
NEW API MANAGER FEATURES:
The API Manager is an increasingly more commonly found on SW architectures. This component, now 3 years old, has incorporated features like:
One of the work focus of the platform is for it to be accessible either for a user role, an advanced developer or a data scientist, and for that disposing of learning material is very important.
For this release we have generated the following guides:
On June 21, our partner Raquel López, IoT Expert Manager of Sofia2 IoT Platform, conducted a webinar titled “Big Data and real time analytics in the IoT” in the framework of the IoT Analytics conference organized by BrightTALK.
In the presentation, which you can access here, Raquel explains why IoT is an excellent business opportunity and addresses various IoT Analytics cases existing in different verticals: Industry, Retail, Health, Energy…
It also delves into capabilities, workflow and modules that make up an IoT platform and Big Data such as Sofia2 and delves into two success stories: Smart Energy and Traceability in Distribution.
You can find the Webinar slides here
Libelium presents a white paper with 50 real IoT success stories after ten years of experience in the market
With the aim to unveil its horizontal approach to the IoT market, Libelium has launched a new white paper to present 50 real smart projects deployed in 120 countries all over the world. The IoT company has summarized its most successful and appealing stories, developed with Libelium technology and its partners ecosystem, for the main verticals of the market. The white paper includes real IoT projects for environment care, water management, precision agriculture, smart cities, parking management, smart building, smart factory, logistics, retail and eHealth.
Libelium’s experience and soundness, with real solutions developed in more than 120 countries with an ecosystem of more than 90 technological companies, have labeled it as one of the market leaders. Alicia Asín, Libelium CEO, and David Gascón, Libelium CTO, analyse in the white paper the position of the company and the short-term trends and challenges that have arisen in the market.
Libelium is recognized in the IoT market to offer the most horizontal and interoperable platform allowing system integrators, software companies and Cloud servers to make compatible its sensor wireless network to more than 40 cloud platforms. “Customers escape from those who try to retain them with vendor lock-in strategies. Transparency has become indispensable for a market that is constantly in motion ”, states Alicia Asín, CEO of Libelium.
RTLS are used to automatically identify and track the location of objects or people in real time, usually within a building or a delimited area. The fixed reference points receive wireless signals from RTLS tags to determine their location.
Examples of real-time locating systems are:
- Tracking automobiles through an assembly line
- Locating pallets of merchandise in a warehouse
- Identification of people for security and safety reasons
- Finding medical equipment in a hospital
The physical layer of RTLS technology is usually some form of radio frequency (RF) communication, like BLE (Bluetooth 4.0), UWB (Ultra Wide Band ) or propietary systems, etc. Tags and fixed reference points can be transmitters, receivers, or both, resulting in numerous possible technology combinations.
RTLS are a form of local positioning system, and do not usually refer to GPS, mobile phone tracking. Location information usually does not include speed, direction, or spatial orientation. Instead they are very cost effective, need minimal batteries, work indoor and outdoor, do not need a mobile telecom operator and use open protocols.
Technologies in Real-Time Location Systems RTLS
There is a wide variety of technologies on which RTLS can be based:
- Infrared (IR). They require a clear line of sight for labels and sensors to communicate, so if a board is covered by a blanket or flips, the system may not work properly.
- Ultrasound. Ultrasound, as a communications protocol, is slower (with longer wavelengths) than the infrared, so it generally can not match the performance of other technologies
- Wi-Fi. Although Wi-Fi infrastructure is often preexisting in the performance environment, accuracy is limited to up to 9 meters, which makes its value as a tool for locating the location is uncertain.
- RFID. There are two types of RFID technologies to consider, active and passive. Passive RFID technology works only in the proximity of specialized RFID readers, providing a ‘point-in-time’ location. As an example, let’s think of a fashion store where the reader sends a radio signal to a labeled item of clothing and an alarm is triggered only when the label is detected very close to the designated control point. With active RFID, it has tags that send the signal to a reader every few seconds (similar to a cell phone and a tower) and triangulation software or other methods are used to calculate the position of the marked object.
- UWB. The advantage of UWB technology is the high level of transmission safety. The UWB signal is difficult to detect and localize, because the spectral power density is below background noise. It can reach an accuracy of 10 centimeters at measuring distances of up to 100 m.
- BLE. The Bluetooth Low Energy (or BLE) appears from the specification in version 4.0. It is aimed at very low power applications powered by a button cell. It has a data transfer rate of 32Mb / s. It operates on frequencies of 2.4 GHz and was created for marketing reasons for smartphone and tablet devices. Important advantages of this technology are that it’s based on a universal standard, and is immediately available on mobile devices without hardware need.
Comparison of Different Technology Tags for RTLS:
It’s available in the latest FEEP IoT & Big Data Platform Sofia2 Release the new functionality to create Ontologies “Creation from JSON / XML”. This option allows you to create an ontology from a file with JSON content or an XML.
We want to create an ontology from our JSON file:
To do this we must follow the following steps:
- We’ll introduce the data to characterize it.
- We’ll select the .json file, press “load attributes in JSON / XML”, choose one of the three registers that appear and select the decimal character.
Finally, we’ll generate the schema and press “load data” to create the ontology.
To create an ontology from an XML file we’ll proceed in an analogous way and will follow the same steps as for the creation through a JSON file.
In the new Sofia2 4.0 release, notebook engine has been migrated to the new Apache Zeppelin version, refactorizing the user interface and including new features and capabilities.
Some of the new notebooks features are:
- Exporting notebooks is now available as JSON file: there are two ways to do this, from user’s notebook list and from edit notebook interface.
- Importation of notebook from JSON files, from the user’s notebook list.
- Exportation of generated data from different kinds of visualization in TSV/CSV format.
- Version control over different repositories like Git, Azure, S3 or ZeppelinHub.
- New visualization capabilities granted by Helium Framework throught many frontend plugins that allow create from new chart types to interpreters.
- Upgraded to Apache Zeppelin 0.7.1 and Spark 2.1
- Centralizated Visualization in notebook execution information (Jobs)
- Notebooks Security improvements