km4city: status and trend, smart city ontology, status, tools and trend

DISIT Lab, Distributed Data Intelligence and TechnologiesDistributed Systems and Internet TechnologiesDepartment of Information Engineering (DINFO)

http://www.disit.dinfo.unifi.it

Km4City: Status and TrendSmart City Ontology, status, tools and trendhttp://www.disit.org/km4cityDistributed Data Intelligence and Technologies LabDistributed Systems and Internet Technologies Lab

Prof. Paolo NesiDISIT LabDipartimento di Ingegneria dell’Informazione Università degli Studi di FirenzeVia S. Marta 3, 50139, Firenze, Italiatel: +39-055-2758515, fax: +39-055-2758570http://[email protected]

Km4City status and progress, March 2016




Km4City


http://www.disit.dinfo.unifi.itKm4CityKnowledge model

for the city



The Km4City Challenge• Huge amount of data are produced from: Open Data, Linked Data, Real Time sensors, Twitter, WiFi, etc. (big data: velocity, variety, volume, veracity, …)– Most of them are not semantically interoperable

• A common model is the only solution to provide services to Public Administrations, Citizens, City Operators (mobility, energy, telecom, etc.)– None of them may have the global view– Cities needs to create a control room with open tools– Integrated competences are needed on a large range of solutions, from ICT, energy, mobility, risk assessment, resilience, etc.




Km4City: Aggregated Data• produce more results than the simple add.

– Offering Aggregated data as a service, API• Enabling risk and resilience assessment• Providing integrated services

– Large companies (as city operators) may have back their data augmented with the data of others stakeholders, plus OD, etc.

– Reduction of costs to make innovative services, facilitating the work for the SME

– Exploiting inference, self correction, reasoning

– reduction of time of adding new data in the integrated environment

– Increasing city resilience and smartnessKm4City status and progress, March 2016



Public ServicesGovern, events, …

Sensors, IOTCameras, ..

Environment, Water, energy

Social MediaWiFi, network

Km4City Smart City Engine

DISCES ‐‐Distributed

and

parallel architecture on

Cloud

Transport systemsMobility, parking

Smart Decision SupportHttp://Smartds.disit.org

Twitter VigilanceHttp://www.disit.org/tv

Flow and Origin Destination MatrixHttp://www.disit.org/odsf

Service map browserHttp://servicemap.disit.org

Smart City Dashboard Http://www.disit.org/dash

Km4C

ity Smart C

ity API

Mobile e Web Apps

Shops, services, operators

User Profiling and Suggestions on Demand

Http://www.km4city.org

Km4City

Tools for Final Users

Tools for Operators

Km4City

Km4City Tools for DevelopersKm4City status and progress, March 2016



• Final Users tools:– Km4City mobile applications– Km4City web application: http://www.km4city.org

• Public administrator tools:– Smart City Dashboards, http://dashboard.km4city.org– ServiceMap Server, http://servicemap.disit.org– Smart decision support system, http://smartds.disit.org– Twitter Vigilance, http://www.disit.org/tv– Traffic and People Flow Assessment http://www.disit.org/6694

• Developers tools: http://www.disit.org/km4city– ServiceMap Server, plus API, http://servicemap.disit.org– Ontology Documentation http://www.disit.org/km4city– LOG LOD browser http://log.disit.org– Open Source Mobile Application, FODD http://www.disit.org/6595

• Back Office tools for Public Administrations– Data Ingestion Manager, DIM, http://www.disit.org/6732– Distributed Smart City Engine, SCE, Scheduler, DISCES http://www.disit.org/6515– RDF Indexer Manager, RIM, http://www.disit.org/6708– RDF store enricher with dbPedia

• Adopted on projects and real scenarios

Km4City EcoSystem




Km4CityMobile App: all stores


http://www.km4city.org

web application




Firenze dove, cosa.. Km4City



http://www.disit.orgRecommender


Chi

Quando e chi

Cosa

Dove come, perché.......



http://www.disit.orgTourists in Florence




http://www.disit.org Hot WiFi in Florence




• Textual search; for example: “Mazzini”Km4City status and progress, March 2016

Km4City In Toscana


http://www.disit.dinfo.unifi.itKm4City Firenze and beyond

• Search all services in the areaKm4City status and progress, March 2016


http://www.disit.dinfo.unifi.itKm4City on Firenze & Tuscany


Road Graph (Tuscany region)132,923 Roads 389,711 Road Elements318,160 Road Nodes1,508,207 Street Numbers

110,374 Services (20 cat, 512 cat.)2,326 Bus stops & 86 bus lines210 Parking areas424 Traffic SensorsInfo on: points, paths, areas, etc.

Dynamic/real‐time• bus lines: 200 updates/day per line• Parking status: 36 updates/day• Traffic Sensors: 48 updates/day• Weather: 2 updates/day for 285 areas• Events: 60 new events/day• Wi‐Fi: 250,000 measures per day



• Areas, Bus lines, bike lanes, tram, RTZ, etc.Km4City status and progress, March 2016

Km4City in Firenze








Km4City EcoSystem




http://www.disit.org

ICT e infrastrutture di comunicazione sono una chiave per tenere sotto

controllo e gestire le

infrastrutturema …. non è sufficiente per migliorare laresilienza delle

città:

Control Room delle Città Metropolitane devono:• arrivare a supervisionare domini multipli e le

interdipendenze fra mobilità, energia, comunicazione, servizi, flussi traffico, flussi pedonali, turismo, etc.

• Migliorare la loro Resilienza, capacità di reazione ed assorbimento.





Decisioni supportate dai datiperiodiche ed in tempo reale

• Condivisione e Integrazione Dati multidominio: semantica e bigdata

• Dati Smart City Engine Control Room• analisi: monitoraggio, flussi e

comportamenti, sondaggi, mining, correlazioni, cause – effetti, etc. – Per il miglioramento di servizi

correnti– Per reagire ad eventi,

incremento della resilienza, – Per la creazione

servizi innovativi– …




Big Data Smart City Architecture


Interoperability

Data IngestionManager

(staticand real time)

Data / info Rendering

Social Vigilance

Km4City

Data Ingestingand mining

Reasoning and Deduction

Data Actingprocessors

Social Media

Peripheral processors

TrafficControl

Sensors Data

Energy centraleHealthAgency

Open Data

…….

Citizens FormationApplications

Distributed processing

Smart City Engine, SCE

Service Map

Linked Open Graph

Smart Decision Sup.

Km4C

ity API

Sugg. and Alarms

Profiled Services

Process In / Data Export

Development

Making DecisionMaking Suggestions

Dashb

oards




Servicemap front end


http://www.disit.dinfo.unifi.itSmart City Decision Support• Smart Decision Support

System based on System Thinking plus

• Actions to city reaction, resilience, smartness..

Enforcing• Mathematical model for

propagation of decision confidence..

• Collaborative work…, • Processes connected to

city data: DB, RDF Store, Twitter, etc.

• Production of alerts/alarms

• Data analytics process• Twitter Processes• reuse, copy past, …




Twitter Vigilance• Public parts accessible on: http://www.disit.org/tv• Monitoring twitter channels with

– high reliability & precision, following slow, fast and explosive events – Multiuser managing multiple: public and private channels – Access to data, advanced search, data analytics, sentiment analysis,

.....• A Twitter Vigilance channel is a set of real time adaptive

searches on twitter. – Each of them may have a complex syntax according to twitter API

and service– Each user may manage a number of channels and searchers

• Active since April 2015 with data collection, since Sept. with big data analytics, since October with Sentiment Analysis– Easy addressing about 600.000 per day– Over than 30 Million of tweets



http://www.disit.dinfo.unifi.itAll Channels (private information)


1) General view with top explosive events on commenting tv Serials

2) This is what there in the ground when the top explosive events are hidden



Twitter Vigilance• http://www.disit.org/tv• Citizens as sensors to

– Assess sentiment on services, events, …

– Response of consumers wrt…

– Early detection of critical conditions

– Information channel– Opinion leaders – Communities – formation




Full text and Faceted Search Facility of Twitter Vigilance db




Twitter Vigilance, >> 500.000 tweets per day





NLP Sentiment Analysis (early results)SA on a channel

SA on a Search


http://www.disit.dinfo.unifi.itTraffic and People Flow Assessment• Origin Destination Matrix

– Specific Sensors, vehicle Kits, mobile App, Wi‐Fi Access Points, etc.

• Assess people and traffic flows to– improve services– predict critical conditions on Crit. Infra.

– take real time decisions and sending messages in push to population

– Increase city resilience– optimize traffic flow– take decision of routing


http://www.disit.org/6694








Km4City EcoSystem





Domini di intervento• Mobilità: inter‐modalità, bigliettazione integrata, sostenibile, scambiatori, sfruttamento stazioni, etc.,

• Servizi: gov ..SUAP, edu, turismo, beni culturali, salute, etc.,

• Energia: risparmio energetico, riduzione amissioni, inquinamento, etc.,

• Ambiente: qualità dell’aria, fiumi, meteo, rifiuti, etc.,

• … commercio, industria, etc.• ... Infrastrutture critiche. resilienza


http://servicemap.disit.org



Smart‐city Ontology• The data model provided have been mapped intothe ontology, it covers different aspects:– Administration– Street‐Guide– Points of interest– Citations from strings– Local public transport– Sensors..– Temporal aspects– Metadata on the data– Statistics– Risk assessment


TemporalMacroclass

Point of Interest

Macroclass

SensorsMacroclass

Local public transportMacroclass

AdministrationMacroclass

Street‐guideMacroclass

PA hasPublicOffice OFFICE

SENSOR measuredTime TIME

SERVICE isInRoad ROAD

CARPARKSENSOR observeCarPark CARPARK

BUS hasExpectedTime TIME

CARPARK isInRoad

ROAD

BUSSTOPFORECAST atBusStop BUSSTOP

WEATHERREPORT refersTo PA

BUSSTOP isInRoad ROAD

ADMINISTRATIVEROAD ownerAuthority PA

MetaData




I Dati• Collezionamento dati statici, quasi statici

e real time, stream– Dati open: geo localizzati, servizi,

statistiche, censimenti, etc.– Dati privati degli operatori: con licenze

limitate per non permettere di fare profitto ad altri operatori sulla base dei loro dati

– Dati personali delle persone: profili, comportamenti tramite APP, IOT, sensori, web, etc.

• Integrazione dati per renderlisemanticamente interoperabili, ed operare deduzioni (time, space… )– I tradizionali collettori di open data danno

visioni statistiche ma non sono adatti a produrre servizi integrati

– Integrazione con modelli semantici unificanti come Km4City



http://www.disit.dinfo.unifi.itService Map Tools





Exploiting Big Data Reasoning

Smart Decision System

Data processing

DISCES Database

DISCES: Distributed SCE Scheduler

Linked Open Graph, Visual Query Graph

Service Map

SCE: Smart City Engine

Km4City RDF Store + indexes:SPARQL End point


Reasoning and Deduction

Web and App

Suggestions and Alarms

Development Interfaces & Srv.

Development Framework

Data Analytics

Data Status web pages

Other SPARQLEnd Points Developers and

Managers

use

development

Low LevelKm4City

API

High LevelKm4City

API

Twitter Vigilance

Information, Data Exploitation,Data Rendering,Profiled Services,Formation, etc.




Service Maphttp://servicemap.disit.org



Linea 4




Km4city ServiceMap Km4City API• http://www.disit.org/6597– REST API: serviceURIor Selection or GPS

– REST API: Query ID– Receive an email– Get a JSON, HTML, …

• EMBED facility in third party web pages



http://www.disit.dinfo.unifi.ithttps://play.google.com/store/apps/deta

ils?id=org.disit.fodd





Fodd, open sourcedemonstrator



Smart‐city Ontologykm4city


>84 Classes>100 ObjectProperties>100 DataProperties

Ontology Documentation: http://www.disit.org/6506http://www.disit.org/6507http://www.disit.org/5606http://www.disit.org/6461



Km4City Ontology and tools• documentation ENG: http://www.disit.org/5606 • documentation ITA: http://www.disit.org/6461• image: http://www.disit.org/6507• ontology .. the OWL and triple version http://www.disit.org/6506

• FODD 2015 app http://www.disit.org/6595• API Service Map: http://www.disit.org/6597• Service Map: http://servicemap.disit.org




http://log.disit.org/spqlquery/




http://log.disit.org


Linked Open Graphhttp://log.disit.org




Linked Open Graphhttp://log.disit.orgA bus stop info….




http://log.disit.org


http://www.disit.dinfo.unifi.itKm4City EcoSystem









Data Ingestion and Mining


Static Data harvesting

Data MappingTo triple

QualityImprovement

Indexing

Real Time Data

Ingestion

StoreValidation

SemanticInteroperabilityReconciliation

Ontologie

triple

triple

‐ Sensors‐ Meteo‐ AVM‐ Parcking

Blog & SN Vigilance

Indexing

Ontologie

RDFStore + indexes: SPARQL

Text MiningNLP

OSIM based toolshttp://osim.disit.orgTwitter VigilanceHttp://www.disit.org/tv

RDFStore + indexes: SPARQL

RDF StoreEnrichment

RDF Indexing ReasoningData Ingestion and Mining

Data MappingTo triple



Example of Ingestion process



http://www.disit.dinfo.unifi.itRDF Store Enrichment, VIP names identification

Km4City status and progress, March 2016http://www.disit.org/5507



OtherSPARQL

End points

Data Ingestion and Mining


DIM: Data IngestionManager

DISCES: Distributed SCE Scheduler

RIM: RDF Indexing Manager

RIM Database and versioning

DIM Database

DISCES Database

Static Data harvesting Data

MappingTo triple

QualityImprovement

Inde

xing

Real Time Data

Ingestion

RDF StoreValidation

SemanticInteroperabilityReconciliation

Km4City Ontology

tripletriple

RDFStore + indexes:

SPARQLEnd point

Distributed Bigdata store

R2RMLModels

Data Ingestion and Mining RDF Indexing

Sporadic: ‐Validation‐Reconciliation‐Enrichment

RDF StoreEnrichment

Reasoning

Data Status web pages

‐ Sensors‐ Meteo‐ AVM‐ Parcking




DIM: Data Ingestion Manager

Km4City status and progress, March 2016RIM RDF Index Manager


http://www.disit.dinfo.unifi.itSmart City Engine• Status: in progress• SLA derived from Cloud SLA• Model mutuated from Smart Cloud Engine of ICARO


Http://192.168.0.45


http://www.disit.dinfo.unifi.itDistributed SCE Scheduler


http://192.168.0.72



Distributed SCE Scheduler


http://192.168.0.72


http://www.disit.dinfo.unifi.itRDF Triples generatedMacro Class Static Triples Reconciliation Triples

Real Time Triples Loaded

Total on 1.5months

Administration 2.431 0 ‐‐ 2.431Metadata of DataSets 416 0 ‐‐ 416Point of Interest (35.273 POIs in Tuscany) 471.657 34.392 ‐‐ 506.049Street‐guide (in Tuscany) 68.985.026 0 ‐‐ 68.985.026Local Public Transport (<5 lines of FI) 644.405 2.385

135.952 per line per day, to be filtered, read every 30 s, they respond in minutes

(static) 646.790

51.111.078

Sensors (<201 road sensors, 63 scheduled every two hours) ‐‐ 4.240

102 per sensor per read, every 2 hours, they are very slow in responding

Parking (<44 parkings, 12 scheduled every 30min) ‐‐ 1.240

7920 per park per day, 3 read per hour,

they respond in seconds

Meto (286 municipalities, all scheduled every 6 hours) ‐‐ ‐‐

185 per location per update,

1‐2 updates per day

Temporal events, time stamp ‐‐ ‐‐

6 for each event 1.715.105

Total 70.103.935 42.257 122.966.893Km4City status and progress, March 2016


http://www.disit.dinfo.unifi.itKm4City EcoSystem• Final Users tools:

– Km4City mobile applications– Km4City web application: http://www.km4city.org

• Public administrator tools:– Smart City Dashboards, http://dsahboard.km4city.org– ServiceMap Server, http://servicemap.disit.org– Smart decision support system, http://smartds.disit.org– Twitter Vigilance, http://www.disit.org/tv– Traffic and People Flow Assessment http://www.disit.org/6694







Km4City Scenarios and adoptions• Km4City is at the basis of real scenarios

– the Florence data aggregator, presented at FODD 2015, February

– http://servicemap.disit.org, see mobile Apps, etc.

• Km4City is adopted in running projects up to 2020– Sii‐Mobility Smart City National, 13.5 Meuro– RESOLUTE H2020 DRS7 project of the EC, 3.8 Meuro– REPLICATE H2020 SCC1 project of the EC, 29 Meuro– …..




• Experimentations and validation in Tuscany• Integration with present central station and subsystems• DISIT lab, Università di Firenze, is the tech-scientific coordinator

Sii‐Mobility


http://www.Sii-Mobility.org

ECM; Swarco Mizar; Inventi In20; Geoin; QuestIT; Softec; T.I.M.E.; LiberoLogico; MIDRA (autostrade, motorola); ATAF; Tiemme; CTT Nord; BUSITALIA; A.T.A.M.; Effective Knowledge; eWings; ArgosEngineering; Elfi; Calamai & Agresti; Project; Negentis

Confidential Km4City status and progress, March 2016

Obiettivi Generali (sintesi)• ridurre i costi sociali della mobilità

per le persone– consentendo minori disagi, maggiore

efficienza, – maggiore sensibilità verso le

necessità del cittadino, – minori emissioni, migliori condizioni

ambientali; – percorsi info‐formativi in modo che il

cittadino cambi le abitudini non virtuose;

– ridurre i costi di trasporto ed i tempi di percorrenza per gli utenti, per i gestori e le amministrazioni, tramite soluzioni di ottimizzazione.


• semplificare l’uso dei sistemi di mobilità– sensori innovativi per AVM e mezzi

privati sul territorio– Sistemi integrati di pagamento e di

identificazione– soluzioni di guida/percorso connesso

(connect drive, smart drive o walk)– Integrazione di dati provenienti da

gestori e sorgenti di tipo diverso– Gestione avanzata di mezzi– misurazione di flussi– realizzazione di sensori, attuatori

• Sperimentazione su comuni e province della Toscana• Contribuire al miglioramento degli standard nazionali ed internazionali




• Develop European Resilience Management Guidelines (ERMG)

– Develop a conceptual framework for creating/ maintaining Urban Transport Systems

• Enhance resilience through improved support of human decision making processes, particularly by training professionals and civil users on the ERMG and the RESOLUTE system

• Operationalize and validate the ERMG by implementing the RESOLUTE Collaborative Resilience Assessment and Management Support Systems (CRAMSS) for Urban Transport Systemsaddressing Road and Urban Rail Infrastructures

– Pilots in Florence and Athens• Adoption of the ERMG at EU and Associated

Countries level


http://www.resolute‐eu.orgUniversity of Florence: DISIT lab DINFO (Projcoordinator), DISIA and DST

UNIFI IT

THALES THALES ITATTIKOMetro ATTIKO GRComune di Firenze CDF ITCentre for Research and Technology Hellas CERTH GR

Fraunhofer‐Gesellschaft zur Förderung der angewandten Forschung e.V.

FHG DE

HUMANIST HUMANIST FR

SWARCO Mizar SWMIZ ITAssociação para o Desenvolvimento da Investigação no Instituto Superior de Gestão

ADI‐ISG PT

Consorzio Milano Ricerche CMR IT




• demonstrate Smart City technologies in energy, transport and ICT in districts in:

– San Sebastian, Florence and Bristol, – follower cities of Essen, Nilufer and Lausanne

• Cities are the customer: considering local specificities

• Solutions must be replicable, interoperable and scalable.

– Integrated Infrastructure: deployment of ICT architecture, from internet of things to applications

– Low energy districts– Urban mobility: sustainable and smart urban

services

1 (coordinator) FOMENTO DE SAN SEBASTIAN FSS SPAIN2 AYUNTAMIENTO DE SAN SEBASTIAN SAN SEBASTIAN SPAIN3 COMUNE DI FLORENCE FLORENCE ITALY4 BRISTOL COUNCIL BRISTOL UNITED KINGDOM5 STADT ESSEN ESSEN GERMANY6 NILUFER BELEDIYESI NILUFER TURKEY7 VILLE DE LAUSANNE LAUSANNE SWITZERLAND8 IKUSI ANGEL IGLESIAS, S.A. IKUSI SPAIN9 ENDESA ENERGÍA, S.A. ENDESA SPAIN10 EUROHELP CONSULTING, S.L. EUROHELP SPAIN11 ILUMINACION INTELIGENTE LUIX, S.L. LUIX SPAIN12 FUNDACION TECNALIA RESEARCH & INNOVATION TECNALIA SPAIN13 EUSKALTEL, S.A. EUSKALTEL SPAIN14 COMPAÑÍA DEL TRANVÍA DE SAN SEBASTIÁN DBUS SPAIN15 CONSIGLIO NAZIONALE DELLE RICERCHE CNR ITALY16 ENEL DISTRIBUZIONE, SPA ENEL ITALY17 MATHEMA, SRL MATHEMA ITALY18 SPES CONSULTING SPES ITALY19 TELECOM ITALIA, SPA TELECOM ITALY20 UNIVERSITA DEGLI STUDI DI FLORENCE UNIFI ITALY: DINFO.DISIT, DIEF21 THALES ITALIA, SPA THALES ITALY22 ZABALA INNOVATION CONSULTING ZABALA SPAIN23 TECHNOMAR TECHNOMAR GERMANY24 UNIVERSITY OF BRISTOL UOB UNITED KINGDOM25 UNIVERSITY OF OXFORD UOXF UNITED KINGDOM26 BRISTOL IS OPEN, LTD BIO UNITED KINGDOM27 ZEETTA NETWORKS ZEETTA UNITED KINGDOM28 KNOWLE WEST MEDIA CENTRE, LGB KWMC UNITED KINGDOM29 TOSHIBA RESEARCH EUROPE, LTD TREL UNITED KINGDOM30 ROUTE MONKEY, LTD ROUTE MONKEY UNITED KINGDOM31 ESOTERIX SYSTMES, LTD ESOTERIX UNITED KINGDOM32 NEC LABORATORIES EUROPE, LTD NEC UNITED KINGDOM33 COMMONWHEELS CAR CLUB CIC CO-WHEELS UNITED KINGDOM34 UNIVERSITY OF THE WEST OF ENGLAND UWE UNITED KINGDOM35 ESADE BUSINESS SCHOOL ESADE SPAIN36 SISTELEC SOLUCIONES DE TELECOMUNICACION, S.L. SISTELEC SPAIN




REPLICATE a Firenze: Energia, ICT e Mobilità



http://www.disit.dinfo.unifi.itKm4City EcoSystem• Final Users tools:

– Km4City mobile applications– Km4City web application: http://www.km4city.org






http://www.disit.org/km4city



Km4City International Actions• DMS2015 for RIM, Vancouver, Canada, Aug. 2015• Cognitive Systems Institute Group Speaker Series, IBM, 2015• SMAU 2015• European Data Forum 2015, Luxembourg, 2015• Smart City 360, Bratislava, Slovenia, 2015• Semantic Challenge: Bethlem, USA, October 2015• Smart City Expo, Barcelona, Spain, 2015• i‐Cities, Palermo, Italy, 2015 • Smart City and Big Data, Italy, Nov. 2015• IEEE Smart City, Cina, December 2015• …• …





Km4city roadmap

2013

Sii‐MobilitySmart City National

‐ Suggestions on demand‐ Dashboards‐ People flow tracking‐ Risk analysis‐ Territorial, areas and paths‐ Environmental: water, hearth,‐ Statistics, Energy, IOT, ..‐ Data Licensing models‐ User Engagement

WeatherCultural Heritage

Energy: recharge pillarWiFi

Events in the city

• http://servicemap.disit.org, API • http://log.disit.org• http://www.disit.org/fodd• http://www.disit.org/tv• http://smartds.disit.org

• Tuscany Map• Services• AVM• Sensors• Parking• …• …

Cultural HeritageEnrichment‐citesEvents in the cityDigitalLocationsFresh places…….

‐Embed‐more API‐iBeacon

SmartDSKm4City App

toda

y

Beta testing‐ Twitter Vigilance

RESOLUTE H2020 2015‐2017Started

‐REPLICATEH2020 2016‐2020‐Sii‐Mobility SCN: *‐20182014 2015

2016



Km4City: Status and TrendSmart City Ontology, status, tools and trendhttp://www.disit.org/km4cityDistributed Data Intelligence and Technologies LabDistributed Systems and Internet Technologies Lab

Prof. Paolo NesiDISIT LabDipartimento di Ingegneria dell’Informazione Università degli Studi di FirenzeVia S. Marta 3, 50139, Firenze, Italiatel: +39-055-2758515, fax: +39-055-2758570http://[email protected]


km4city: status and trend, smart city ontology, status, tools and trend

Technology

distributed data intelligence

esdisit lab

internet technologies