Snap4City 6/2024 Digital Twin services and tools offering catalogue

In the following, a Selection of the main Digital Twin offers of Snap4City solutions and applications for the 2024.
Please contact snap4city@disit.org for any additional offer and evetual declinations, customizaton, combinations, etc.

Mobility and Transport Domain

• Goals:
  • Decongestion
  • Decarbonization
  • Accessibility to services
  • Security/Safety of city users
• Solutions for Operation (monitoring, managing, mobile apps, digital signages, control rooms)
  • Monitoring traffic, parking, people flow, services, boats, ports, beaches, etc.
  • Early detection/warning of critical conditions: traffic, congestion, security/safety
  • Managing Smart Parking, transportation services, fines, etc.
  • Managing fleets: personal, sharing, waste collection, maintenance, etc.
  • Managing E-sharing, pooling services, MaaS, etc.
  • Managing entrances in city areas: restricted areas, touristic busses, etc.
  • Production of suggestions, resommendations, nudging 
  • Computing predictions of any kind
• Solutions for Planning (optimization and what-if analysis)
  • Reduction of traffic congestion, via optimization: semaphore cycles, viability, routing
  • Reduction of Pollutant Emissions, via optimization: semaphore cycles, viability
  • Optimization of transportation offers wrt multimodal mobility demand
• Algorithms and computational solutions
  • Optimisation of viability of an area for reducing congestion, waiting time, stops
  • Optimisation of semaphores time cycles, synchronization, in an area for reducing congestion, waiting time, stops
  • Predictions for: traffic flow, smart parking, smart bike sharing, people flows, etc. (ML, DL)
  • What if analysis: routing, traffic flow, demand vs offer, pollutant, etc. (Simulation + ML)
  • Traffic flow reconstruction from sensors and other sources (simulation + ML)
  • Public Transportation: Ingestion and modelling of GTFS, Transmodel, NeTEx, etc. (DP)
    • Analysis of the demand mobility vs offer transport of according to public transportation and multiple data sources (Simulation)
    • Assessing quality of public transportation (analysis)
  • Accidents heatmaps, anomaly detection (analysis, ML)
  • Road light controlled by traffic conditions
  • Tracking fleets, people, via devices: OBU, OBD2, mobile apps, etc. (DP)
  • Routing and multimodal routing (multistop travel planning), constrained routing, dynamic routing (DA)
  • Computing Origin Destination Matrices from different kind of data (analysis, DP, DP)
  • Computing typical trajectories on the basis of tracks (analysis, ML)
  • Fleet management, monitoring,  booking, allocation, maintenance
  • Computing Messages for Connected drive (DP)
  • Slow and Fast Mobility 15 Minute City Indexes (analysis, DP, …ML)
  • Computing and comparing traffic flow on devices and at the city border (analysis)
  • Typical time trends for traffic flow and IoT Time series. (analysis, ML)
  • Impact of COVID-19 on mobility and transport
  • Computing SUMI, PUMS, etc. (mainly DP)
  • Definition of Scenarios: traffic, road graph, conditions, etc.
  • Etc.

City Users Domain

• Goals:
  • Quality of Life, quality of services
  • Costs reduction of services
  • Accessibility to services: citizens, Tourists, commuters, etc. 
  • Security/Safety of city users
• Solutions for Operation (monitoring, managing, mobile apps, digital signages, control rooms)
  • Monitoring services: tickets, reputation, usages, areas, etc.
  • Monitoring user behaviour: indoor/outdoor, hot places/services, ports, beaches,
  • Computing: origin destination, trajectories, travel means, etc. 
  • Early detection/warning of critical conditions, connection with Video Management Systems
  • Managing entrances in city areas: restricted areas, touristic busses, etc.
  • Production of suggestions, recommendations, nudging to city users and operators
  • Providing Virtual Assistants for City Services, Tourist Offices, etc.
  • Monitoring reputation of services via: social media, blogs, etc.
  • Collecting complains, requests, participations from City users via mobile apps
  • Computing predictions of any kind
• Solutions for Planning (optimization and what-if analysis)
  • Reduction of Pollutant Emissions, via optimization
  • Optimization plan to distribution of workload on multiple touristic offers/services, area cleaning, etc.
  • Predicting reputation of services, touristic and operative
• Algorithms and computational solutions
  • People detection and classification: persona, strollers, bikes, etc. (ML, DL)
  • people counting and tracking, head counting, people trajectories (via thermal cameras, ML, DL)
  • People flows prediction and reconstruction, (ML, DL)
    • Wi-Fi data, mobile apps data, Mobile Data, etc.
  • User’s behaviour analysis, People flow analysis from PAX Counters and heterogenous data sources (ML, AI)
    • origin destination matrices, hot places, time schedule,
    • Recency and frequency, permanence, typical trajectory, etc.
  • Computing User engagement and suggestions for sustainable mobility (Rule Based, ML)
  • Social media analysis on specific channel, specific keywords: see Twitter Vigilance,
    • Reputation, service assessment: MultiLingual NLP and Sentiment Analysis, SA
    • Tweet proneness, retweet-ability of tweets, impact guessing
    • Audience predictions on TV channels and physical events, locations
    • Prediction of attendance of events and on attractions
  • Virtual Assistant construction, LLM, NLP, Sentiment Analysis (DL, NLP)
  • Video management System integration for security
  • 15 Minute City Index , etc. (modeling and computability)
  • Computing SDG, etc., (DP)
  • Etc.

Environment, waste, land, etc., Domain

• Goals:
  • Reduction of pollutant emissions and EC taxations
  • Cost Reduction for waste collection, reduction of waste collection impact on mobility
• Solutions for Operation (monitoring, managing, mobile apps, digital signages, control rooms)
  • Monitoring emissions, weather, waste, water, etc.: sensors, traffic, flows, ….
  • Early detection/warning of critical conditions on emissions, weather, waste, water, fire, animals, …
  • Early detection/warning of critical conditions for landslides, water flooding, beach
  • Managing Smart Waste: bins/lockers, waste collection daily plan, pay as you throw, PAYT, etc.
  • Short terms prediction of emissions: CO2, NO2, etc.
  • Production of suggestions, nudging 
  • Computing and predicting long terms KPI indicators of the European Commission
• Solutions for Planning (optimization and what-if analysis)
  • Identification of main CO2/NO2 emission locations in the city, total production from traffic
  • Reduction of Pollutant Emissions, via optimization: semaphore cycles, viability
• Algorithms and computational solutions
  • Pollutant Predictions: short, long and very long term European Commission KPIs
    • NOX, PM10 pollution on the basis of traffic flow, 48 hours (ML, AI, DL)
    • Cumulated NO2 average value over the year, ……. (ML, AI, DL)
  • Computation of CO2 on the basis of traffic flows (DP), computing emission factor (DA)
    • each road for each time slot of the day
  • Prediction of MicroClimate conditions for diffusion (ML, AI)
    • NO2, PM10, PM2.5, etc.
  • Prediction of landslides, 24 hours in advance (AI, DL)
  • Heatmaps production, dense data interpolation (DP) for
    • Weather conditions: temperature, humidity, wind, DEW
    • Pollutants and Aerosol: NO, NO2, CO2, PM10, PM2.5, etc.
  • Impact of COVID-19 on Environmental aspects (DP)
  • Optimisation of waste collection schedule and paths (DP, ML)
  • Computing SDG, SUMI, PUMS, .. (mainly DP)
  • Etc.

Snap4Building Domain

• Goals:
  • Efficiency, costs
  • Accessibility to services
  • Security/Safety
• Solutions for Operation (monitoring, managing, mobile apps, digital signages, control rooms)
  • Monitoring usage, energy consumption, environmental conditions, people flows, services, etc.
  • Early detection/warning, alarm, of critical conditions
  • Production of suggestions, nudging 
  • Managing smart services: cabinets, dispenser, lockers, etc.
  • Global and local 3D/2D representations of area and buildings
  • Integration with Video Management Systems
  • Computing predictions of any kind
• Solutions for Planning (optimization and what-if analysis)
  • Reduction of energy costs, via optimization
• Algorithms and computational solutions
  • Digital Twin for monitor, control and manage distributed infrastructures
    • 2D/3D representations of the whole set of buildings, BIM modeling
    • Entities (building, floors, rooms, parking, charging stations, gates, etc.) with their shapes and descriptors, and data monitoring  the allocation to office, meeting, cafeteria, storage, stairs, elevator, etc.
  • Monitoring and computing KPI on real time for
    • energy consumed or produced (hot/cold), parking, logistic, presences, cleaning, air quality, departments, subareas, maintenance, etc.
    • allocation/designation, dispositions, heating, cooling, temperature, equipment, etc.
    • grouped in Zones

Energy Domain

• Goals:
  • Efficiency, costs
  • Accessibility to services
• Solutions for Operation (monitoring, managing, mobile apps, digital signages, control rooms)
  • Monitoring energy consumption (heating, cooling, prod.,..), conditions, charging stations, etc.
  • Managing Smart Light for city: dimering, programming, traffic control, controllers, legacy, etc.
  • Early detection/warning, alarm, of critical conditions
  • Managing smart services: cabinets, lockers, etc.
  • Production of suggestions, nudging 
  • Global and local 3D/2D representations of area and buildings
  • Managing Communities of Energy, certification via Blockchain
  • Computing predictions of any kind
• Solutions for Planning (optimization and what-if analysis)
  • Reduction of energy costs, via optimization
  • Identification of roofs with better orientation
  • Optimization of battery storage size for PV plants
  • Community of Energy planning and viability
• Algorithms and computational solutions
  • Monitoring Energy Consumption in single building, area and per zone
  • Matching Energy consumption with respect to the actual usage
  • Computing Roof orientation for Photovoltaic installations
  • Optimisation of Photovoltaicc installations to identify the best parameters of size and storage
  • Smart Light management, unicast and multi cast management, smart light controlled by traffic flow data
  • Collecting and managing Communities of Energy
  • Monitoring Energy provisioning on recharging station
  • Optimization of battery life
  • Computing KPI
  • Etc.

Assets Quality Control Domain

• Goals:
  • Efficiency, costs
  • Quality Level
• Solutions for Operation (monitoring, managing, mobile apps, digital signages, control rooms)
  • Monitoring :
    • Assets: switches, Wi-Fi, servers, UPS, sensors, building, TV Cams, etc.
    • Energy: consumption, operative conditions, etc.
    • Production: continuous quality analysis
    • Etc.
  • Early detection/warning, alarm, of critical conditions
    • Multichannel Event reporting: email, Telegram, mobile apps, SMS, etc.
  • Managing maintenance operation
  • Computing predictions of any kind
• Solutions for Planning (optimization and what-if analysis)
  • Reduction maintenance costs, reduction of critical SLA conditions, improvement of quality level

Industry production Domain

• Goals:
  • Efficiency, costs
  • Production optimisation
  • Quality Level
• Solutions for Operation (monitoring, managing, mobile apps, digital signages, control rooms)
  • Monitoring KPI: administration, production, commercial, faults, etc.
  • Early detection/warning, alarm, of critical conditions
    • Multichannel Event reporting: email, Telegram, mobile apps, SMS, etc.
  • Managing maintenance operation, predictive maintenance
  • Computing predictions on KPI
  • Computing predictive maintenance
  • generation of patterns in production, design, etc.
• Solutions for Planning (optimization and what-if analysis)
  • Generative AI and predictive AI for production plan optimisation
  • Reduction maintenance costs, reduction of critical SLA conditions, improving quality level