ACQUA 4.0

The aim of “ACQUA 4.0” Research and Development project, which was co-funded by the POR Tuscany, was to develop a prototype of an innovative system designed to assist managers of the Integrated Water Service in achieving a more environmentally sustainable management of water resources. The objective of this prototype is threefold: to reduce water, energy consumption and costs, and optimise the service offered.

The Acqua 4.0 project has developed a predictive model that exploits radar technologies, both satellite (SAR) and terrestrial, to monitor Earth movements, such as landslides. This model enables the identification — and, in some cases, prediction — of damaged water conduits that may cause water waste.

Green

SM.A.R.T.

SM.A.R.T. (SMart Analytics in Roads and Transportations) research and development project was designed to address the requirement of both individual citizens and public administrations for intelligent mobility services that are accessible, dynamic and contex-aware.

The main objective of SM.A.R.T. is to develop an integrated platform of Predictive Analytics services and supporting sensors (IoT sensors) for the extraction of insights from multiple sources. This facilitates enhancement of urban services in the context of Smart Mobility in a smart city, with a particular emphasis on viability, traffic management and smart parking.

To achieve the above, Hesplora developed a predictive model that uses machine learning algorithms to predict the likelihood of finding a parking space on a given street, as well as a graphical interface that allows citizens to use the system quickly and intuitively. A monitoring dashboard was also created, containing KPIs and insights that have been modelled and extracted from sensor data.

Gold Red

RAN Monitoring

The aim of the project is to provide key performance indicators (KPIs) and raw monitoring counters, as well as inventory and analysis for the mobile network services and FWA (fixed wireless access) by Fastweb. The system must be capable of integrating and be compatible with Fastweb’s data architecture, which is based on Amazon Web Services (AWS).

The solution includes the following features:

• Data management, data ingestion, retention and organization
• Data consistency, Data quality checks and its derivatives
• Data analysis, production of views, enrichment, correlation and aggregation of KPIs e counters

The solution was integrated with the customer’s Data Lakehouse. It collects, via ETL (Extract, Transform and Load) pipelines, coverage and connectivity data of the cellular net from the customer’s cellular network, as well as data from the Radio Access Network (RAN) processed as both raw counters and KPIs.

The data life cycle was managed in terms of persistence, durability and retention policies. Specific checks were developed to assess and improve data quality. Furthermore, data enrichment techniques were employed to obtain additional geographic information, grouping it according to population density and targeted indices over chosen time periods.

For some sources, geo-referenced information was used, allowing both geographical clustering of data and clustering based on population density. In other cases, time-based aggregations and transformations were required to calculate KPIs and indicators.

At the end of the process, the data is available for consumption by two different types of users:

• Business Users: through Tableau dashboard
• Technical Users: through query engine (AWS Athena) for advanced exploratory analysis.

Red

Asset Intelligence

On behalf of Posteitaliane, we successfully built an asset intelligence system as part of a two-year programme. The objective of the system was to align and, when necessary, reconcile the logical views of technological assets – based on company data from various information systems – with their actual state in the physical world.

The project, developed within the client’s Azure cloud tenant, led to the construction of a Data Lake capable of collecting, cleaning and correlating all data regarding technological assets (ticketing systems, discovery, inventory, logistics, etc.) to build a unified view that is as close to reality as possible. The project involved the management of a substantial dataset relating to approximately 1 million active technological assets. The data is centralized within a Data Lake that is populated daily via pipelines made of Spark jobs responsible for:

• Data Ingestion​
• Data Cleaning ​
• Data Quality​
• Data Correlation​
• Data Reconciliation ​

The processed data is organised into views and repositories storing business-ready data, which is itself ingested by BI, dashboarding and reporting tools as well as feeding automated reconciliation flows for misaligned data directly into affected systems.

As part of the project, a discovery agent was also developed to collect data from devices connected to each workstation, with the aim of replacing the existing asset discovery systems.

Red

Forestry Analyzer

Climate change is one of the greatest challenges facing mankind in recent centuries. Deforestation has been demonstrated to have a significant impact on climate change, global biogeochemical cycles and biodiversity loss.

According to estimates from the IPCC (Intergovernmental Panel on Climate Change), forests and their degradation and deforestation processes are responsible for 20% of total anthropogenic greenhouse gas (GHG) emissions: reducing these emissions will be necessary to avoid dangerous climate change.

Slowing or stopping deforestation is an economical and short-term solution to effectively reduce global emissions, with extraordinary additional benefits for biodiversity and sustainable development in tropical countries.

The Forestry Analyzer project, carried out by Hesplora and co-funded by IFAB, allowed to develop a platform for analysing historical trends in deforestation and carbon dioxide emissions and predicting their future development. To achieve this goal, Hesplora’s researchers used Machine Learning (ML) algorithms, which have shown great effectiveness in this field and can harness the potential of “big data” obtained from satellite observations. Regarding satellyte data, Hesplora chose to enhance the value of EU-funded investments by using the satellite image provided by Copernicus from the European Space Agency (ESA).

Green

PPM (Process Performance Management)

The PPM (Performance Process Management) project is an advanced reporting tool that uses KPIs to analyse the operation of a bank’s internal business processes.

The system uses all the fundamental principles of Performance Management. The architecture, which is entirely based on Microsoft technology (SQL Server, Analysis Services, Tabular, Power BI) and collects data of various types, aggregates it and displays it using specific KPIs. The visualisation of the data by the users is managed through both horizontal profiling (by area of expertise) and vertical profiling (user hierarchy level).

Gold

Operatore 4.0

Hesplora is a partner in the Operatore 4.0 project, which aims to develop an ICT Infrastructure for planning interventions on electricity, gas and water distribution networks, integrated with the field operator. The latter is equipped with a cyber-physical system with smart sensors, intelligent operation and augmented reality (according to the Industry 4.0 model), which allows the operator to request useful data and information without using his hands and to receive them both through images displayed with glasses and through texts reproduced via TTS (Text To Speech).

Essentially, Hesplora has responded to the need to provide information support to field operators through technology that allows them to work hands-free with a highly innovative design component.

To achieve this goal, our researchers have used two cutting-edge digital technologies in a synergistic manner: Augmented Reality (using smart glasses) and Natural Language Voice Interfaces. 

This project is co-funded by the POR-CReO FESR 2014-2020 funds - part of the RDI Call 1, which is a call for aid for investment in research, development and innovation.

Red

PA Customer Service

The PA customer service project focused on analysing and optimising of customer service for a leading company in the public administration sector. The deployment of advanced Process Mining technologies enabled real-time monitoring of citizen interactions, facilitating the identification of inefficiencies and areas for enhancement. The implementation of Celonis, a leading process mining software, offered a comprehensive and precise overview of operations, swiftly pinpointing critical areas and enabling the execution of targeted solutions to enhance overall efficiency.

By visualizing operational flows clearly, corrective measures were proposed to reduce response times, optimise the management of resources, and enhance the customer experience. This approach has the dual benefits of reducing operating costs and improving the quality of service, directly impacting user satisfaction.

The result was a more efficient, responsive, and forward-thinking Customer Service, capable of aligning more closely with citizens’ needs and corporate goals.

Gold

Process Mining Monetica

On behalf of Posteitaliane, approximately 20,000 practices were analysed over a 15-month period to determine the full acquiring process relating to the activation of new POS. The project was overseen by the COO (Chief Operating Officer) of Posteitaliane and was closely monitored and managed by the company’s dedicated process quality centre.

By leveraging Process Mining and automated discovery methodologies, we have developed a process model, which was subsequently analysed in order to identify potential optimisations. These insights will then undergo a what-if analysis session to assess their feasibility and impact.

Two distinct scenarios were identified and simulated, starting from the generated process model. Various adoption thresholds were also applied to the individual scenarios and the combined ones, in order to evaluate their impacts in advance.

The what-if analysis mentioned above enabled the evaluation of the cost-benefit ratio of the two chosen variants of the process. The evaluation was based on the variation of their implementation threshold and the adoption of the process itself.

A further positive impact on the customer was to have enabled the internal competence centre on process quality to be equipped with new data-driven tools and techniques.

Gold

Smart Water Network

On 25 May 2016, approximately 200 metres of Lungarno Torrigiani in Florence, located near Ponte Vecchio, suffered a sudden collapse due to a pipe failure. Following this event, Publiacqua, in collaboration with Ingegnerie Toscane, decided to conduct a subsidence analysis technique using SAR satellite imaging technology.

Hesplora, with the support of Aresys (a spin-off of the Politecnico di Milano), analysed satellite images (SAR Sentinel satellite) from January 2015 to March 2017. The analysis showed that no ground movements had been detected prior to the collapse, providing evidence that contradicts the initial theory that attributed the pipe breakage- and the subsequent collapse of the Lungarno section - to a landslide.

In addition, an experiment was conducted in Prato to assess the relationship between ground movement and water loss.

Green

SENECA

Project SENECA (Sistema IntElligente per l’ottimizzazioNe delle infrastrutturE di parcheggio e riCarica, e per il supporto alla guidA virtuosa) developed and tested Smart Mobility solutions that, when integrated with the Borgo 4.0 platform, was able to optimise the use of parking and charging points. These solutions increased road safety and improved the environmental sustainability of mobility.

Hesplora carried out the definition and specification of the driver behaviour analysis component, using Computer Vision and AI to develop Gamification methods and tools specifically aimed at professional drivers, to encourage virtuous behaviour in a simple and enjoyable way.

POR Campania FESR 2014/2020 O.S. 1.1 Az. 1.1.4 Avviso per la selezione della Piattaforma tecnologica di filiera – Mobilità sostenibile e sicura – Piano C – Piano progettuale per il sostegno alla sperimentazione di modelli e a progetti di innovazione derivata – CUP B32C18000280007.

UNIONE EUROPEA
Fondo Europeo di Sviluppo Regionale

Gold Red

SIM (Sistema Integrato di Monitoraggio ambientale)

This project is part of the initiatives promoted by PNRR and Ministero dell’Ambiente e della Sicurezza Energetica (MASE). The Environmental Monitoring System (SIM) is an essential tool for anticipating, preventing, controlling and managing emergencies in various fields, including air quality, forest fires, landslides and water quality.

A system of this complexity is based on a variety of information sources from across the entire country, including public administration documents, satellite images and drones. Such a large and various data requires high quality in the collection, processing and cataloguing phases, as these actions directly affect the reliability of the results provided by the system.

Within the specified context, Hesplora plays an important role in the realisation of the Data Platform by overseeing the study, validation and cataloguing of the data used within the SIM.

Our team of experts accurately mapped data sources to ensure effective organisation, analysing types and availability.

The data catalogue was defined on the basis of the information tracked by the respective fields’ experts, and the creation of metadata was automated using advanced generative AI techniques.

Green

Monitoraggio Acquedotto dell'EUR

EUR S.p.A. is responsible for the management of an irrigation and fire-fighting aqueduct that covers the entire EUR district. This network comprises over 100 km of pipes that distribute water from artesian wells to more than 400 private users, feed EUR’s monumental fountains, allow the watering of the district’s public gardens and supply more than 130 fire hydrants.

This water supply network is comparable in complexity to the aqueduct of a medium-sized city. Hesplora designed a state-of-the-art monitoring system for EUR SpA, providing constant supervision of the infrastructure; this helps guiding interventions to improve the network and to develop a service approach that maximizes the value of the asset.

The project also resulted in the development of a model that, not only enhances the understanding of the infrastructure, but also supports the definition of a districting hypothesis, laying the groundwork for more efficient network management.

Green

AGWD

The AGWD system, developed by Hesplora for ENI (through a subcontract with Reply) in collaboration with Cineca, operates according to the methodology of “Gas While Drilling” (GWD), based on the analysis of gas components present in the drilling mud, aiming to identify the gas types (and even fluids) found in the formation. Its strategic function is to analyze and calculate the main characteristics of these gases, with precise visualization, to support the interpretation of the collected data.

The AGWD, fully developed in C++ with Qt for the GUI, acquires information from the Eni datalake using Hadoop logic.

Green

Revisione Processo Sinistri

On behalf of a major insurance company (with approximately 11 billion in direct collection, 10 million customers and 10,000 agencies and sub-agencies spread across the country), and in close collaboration with the claims department, we analysed single and double signature claims. This was done as part of an initiative to streamline internal processes for a total of more than 100,000 practices over a 6-month period.

Using advanced Process Mining techniques and working closely with the client, several key parameters were identified, including the territorial basis, the method of settlement of the claim, the existence of a claim for damages, the consistency of the reconstruction between the parties and the channel for opening the claim.

The initiative enabled the complete reconstruction and modelling of the processes under review, creating specific models for each dimension of analysis, measuring each identified phenomenon and weighing the associated inefficiencies in terms of their real impact on the business.

The differences in the implementation of the process at territorial level were highlighted. A number of considerations were identified regarding the rewards for the network of experts and liquidators, as well as unexpected inefficiencies and emerging best practices, which have been confirmed by recent organisational recalibrations for some cells in the territory.

Following the analysis, the customer introduced several improvement initiatives, such as change requests to the applications supporting the process, random checks and changes to the weights of some process parameters.

Gold

APOLLON

APOLLON (environmentAl POLLutiOn aNalyzer), project co-funded by POR Puglia, aims to develop and test innovative methods and tools for monitoring environmental quality in urban settings, with a specific focus on air and noise pollution, and on ultraviolet (UV) rays.

The approach adopted is characterized by the low cost of establishing the sensor network, its extensive distribution throughout the territory, and the proactive involvement of students, citizens and public administrations.

For the APOLLON project, Hesplora was responsible for building the IoT infrastructure for the detection of environmental parameters, including the design and construction of fixed and mobile control units with on-board sensors.

In addition, Hesplora developed a mobile crowdsensing application, an innovative approach that involves the use of smartphone sensors or special devices equipped with sensors to enable citizens to collect environmental data.

Green