Scroll through and explore these exciting next-generation application in various stages of development. All these applications use next-gen technologies like software-defined networking, local cloud and gigabit to end-user and are transforming how we live, work, learn and play. If you have an application you would like to include in this growing list, please following the instruction below and join the US Ignite community.
OrangeCone is a Citizen Engagement tool that creates a real-time conversation about public spaces between Citizens and their Governments
GreenStar Network is the world's first neutral carbon network in the world, linking green nodes in Canada and internationally.
Sensus is a cross-platform (Android, iOS, and Windows Phone) system for mobile crowd-sensing.
A distributed cloud built from desktop machines at the edges of the internet. You can think of it as AirBNB for your computer.
Collaborative Adaptive Sensing of the Atmosphere is a new paradigm to observe the lower part of the atmosphere to better warn the public of severe weather threats (e.g., tornados, flash floods) with the ultimate goal to safe lives and property. This goal is achieved by creating closed-loop networks of small, low-cost radars that scan close to the ground. With these networks the atmosphere can be scanned in much finer spatial and temporal resolution than with the current, operational radar system. These features enable forecasters to give earlier and more precise warnings in the case of severe weather. The CASA system relies heavily on the Internet to transmit data from and to the sensors. Advanced networking is essential in this case, since the control-loop of the system requires low latency and the radars can transmit data of up to 150 Mbps each.
The interdisciplinary eldertech team at the University of Missouri has been investigating the use of in-home sensor technology and machine learning to detect early signs of illness and functional decline, as a strategy towards proactively managing chronic health conditions. The sensor network includes passive infrared motion sensors, a bed sensor that captures quantitative pulse, respiration, and restlessness while positioned under the mattress, and gait analysis/fall detection systems using vision, radar, acoustic arrays, and the Microsoft Kinect depth camera. Automated health change alerts are generated and sent to the clinical staff, based on recognized changes in the sensor data patterns. The speaker will describe experiences in using the sensor network since 2005 at two sites and will offer insights into the impact on the healthcare system and how US Ignite can help.
Interactive collaboration with video, voice and graphics from several locations all layered together, visually organized into a real size, real time, intuative work platform.
Our service allows remote users to access a suite of software applications over ultra high speed networks.
Brief Description: Using Data Captured in public space through sensors like video and sound to understand what is happening in the streets. Combining the data with sentiment analysis on Social Media allow for early warning of possible incidents to the police surveillance room. This all to prevent escalation of incidents in an early stage Challenges and Solutions: Defining the right algorithms, connecting the dots between sound , movements and sentiment. How is this perceived by the public, does it fit with Privacy regulations. Can we extend this system throughout a city or event to multiple cities. Major Requirements: Through a PPP with the city of Eindhoven, the police and the technology companies it is possible to work jointly on innovations and get the residents and entrepreneurs to cooperate. DITSS is the PPP to combine all this and oversee the project. Get Universities involved to study the Privacy and support development of algorithms Performance Targets/ Key Performance Indicators (KPIs): - Less incidents at Stratumseind (Eindhoven) - More divers pub offering - Better economy for entertainments district Measurement Methods: - Police registration in incidents - Ongoing communication with pub owners - Ongoing communication with visitors Standards/Interoperability: - Connecting various data sorts into one environment based on FIWARE. Although algorithm based analytics is done at the edge the data is needed for development of additional algorithms and tro support as evidence when needed Replicability, Scalability, and Sustainability: The connection layer for sensors is through a smart lighting grid where FIWARE is used to provide an urban data platform in the cloud. Project Impacts: Less incidents in a pub street is providing a safer place attracting more people; developing and demonstration this sensor technology has raised interest globally to the region of Eindhoven allowing the local partners specialized in video and sound to grow their business. The usage of a smart lighting grid connects The City of Light (Eindhoven) to a great deal of LED streetlight networks currently implemented. Demonstration/Deployment Phases: first developments started in 2015. Phase I Pilot/Demonstration June 2016: Extend the sensor network to Smart Lighting Grid. FIWARE nodes available. Further development of algorithms. Phase II Deployment June 2017: Extend sensor network to Mobile Edge Cloud to support easy installation of sensors at any city.
Brief Description: Eindhoven is one of the six Dutch cities that signed the Open and Agile Smart Cities (OASC) letter of intent to join an initiative that will create smart cities based on the needs of cities and communities. Eindhoven wants to accelerate the smart city wave by adapting the FIWARE platform. In the LivingLab Stratumseind and other fieldlabs Eindhoven needs a smart city platform: to cope with the data and organize the traffic of the information. Challenges and Solutions: For the collecting of data in the public space in the Livinglab Stratumseind in Eindhoven (and other fieldlabs), transport, storage, sharing, analyzing, and use of these data and the information a smart city platform is developed that fits the goals of the LivingLab Stratumseind and can be a model or standard to cope with data in smart cities : practical, supporting the public private collaboration in the LivingLab Stratumseind on public safety, interoperability, avoiding vendor lock-in, supporting comparability. We want to develop a practice that can easily be shared. FIWARE is used to provide an urban data platform in the cloud. Major Requirements: Partnership of the city of Eindhoven with other governmental partners, business partners and knowledge partners in a PPP that is already working on issues as the public safety, attractiveness and livability of Stratumseind has to be enlarged with a smart city platform that enables these partners and other parties to develop smart solutions. Performance Targets/ Key Performance Indicators (KPIs): - A smart city platform that supports the development of smart solutions in the LivingLab Stratumseind - The platform can manage the data collected in the LivingLab, open data, archived and real time data - The platform will facilitate innovation by the partners and, as much as possible, by other parties by making data publicly available and enabling access through open interfaces. - Measurement Methods: - Compliant with the City of Eindhoven Smart Society Charter: IoT Architecture principles & guidelines (under construction) Standards/Interoperability: Connecting various data sorts into one environment based on FIWARE. Replicability, Scalability, and Sustainability: A modular architecture with open interfaces as the core of the IoT or data-driven development to ensure interoperability and facilitate re-use and cooperation. A smart city data platform in the cloud Impacts: The smart city platform will bring in a dashboard with information and insights that is supporting and stimulating the development of smart solutions for public safety in the Stratumseind in Eindhoven: less incidents, a safer place, attracting more people. The platform will stimulate the global interest to the region of Eindhoven allowing the local partners in the PPP to grow their business. Demonstration/Deployment Phases: first developments started in 2016.
Description: The Seattle Department of Transportation is working internally and with Microsoft, the nonprofit DataKind, and data scientists from University of Washington, Microsoft Research, HERE Maps, and others to use data to predict crash probabilities, with the goal of reducing bicycle and pedestrian fatalities and serious injuries to zero. Challenges and Solutions: Seattle’s Vision Zero Plan lays out an aggressive goal to reach zero traffic-related deaths and serious injuries by 2030. More than 30 crashes occur every day in Seattle and transportation-officials generally evaluate crash locations for safety improvements after the fact. Through this research, Seattle intends to create predictive models that will allow the City to take a systemic approach and proactively improve safety. Major Requirements: 1. Collect and clean datasets. 2. Identify factors that commonly contribute to collisions. 3. Apply findings citywide to create predictive models. Performance Targets/ Key Performance Indicators (KPIs): • Eliminate transportation-related serious injuries and deaths by 2030 • 10 percent reduction in fatalities and serious injuries annually Measurement Methods: Describe the methods to measure the performance/KPI impact to assess the benefits to the residents/citizens. • The Seattle Department of Transportation (SDOT) will continuously maintain collision records and post progress toward our goal on a public-facing performance dashboard. Standards/Interoperability: Cities often have similar infrastructure challenges. By understanding which factors are the greatest predictors of crashes, any city can improve its urban design for safety. Replicability, Scalability, and Sustainability: The collision factors identified through data-analysis could easily be shared with other government entities for use at the local, state and federal levels. In addition, SDOT will develop a model to refresh output annually. Impacts: AAA and the Centers for Disease Control and Prevention estimate that each serious collision costs society approximately $6 million in the deployment of emergency resources, traffic congestion, insurance claims and lost wages. For Washington State, that translates into about $700 million annually. Reducing crashes will save lives, reduce congestion, lower the monetary and reduce burdens on first responders. Demonstration/Deployment Phases: Phase I Pilot/Demonstration June 2016: DataDive with DataKind, Microsoft, and University of Washington: Presenting initial results Phase II Deployment June 2017: Using the findings from our research partnership, implement predictive collision modelling and begin applying engineering countermeasures based on outputs.
Description: - Shirahama is a town of about twenty thousand people on the Pacific coast having a beautiful beach with white sands, attracting more than three million tourists. Nealy 10 % are inbound, demanding free Wi-Fi Internet service. - Shirahama, on the other hand, has to prepare for earthquakes and tsunamis because it is officially said the probability of a large, M8-M10 class earthquake occurring within 30 years is approximately 70%. - The project aims at clarifying the effectiveness of a resilient communication platform called NerveNet, developed by NICT, which provides resilient local communication as well as connectivity to the Internet. Challenges and Solutions: - Ensuring communications and information sharing among residents and tourists even if public networks and the Internet become unavailable due to disasters by introducing a resilient communication platform "NerveNet" since sometimes when great disasters happen Major Requirements: 1. Achieving a consensus among the project team, local authorities, organizations, and residents on the necessity of doing the pilot test for preparing for disasters and anticipating economic benefits of tourism 2. Designing the pilot test such as the configuration of the network, the applications running on it, and the locations of devices to be installed. 3. Developing the system (devices and applications), installing it (many devices must be installed outdoor), and testing it. 4. Operating it and measuring data 5. Achieving a consensus on the benefits of the system 6. Sustainable operation of the system by the town Performance Targets/ Key Performance Indicators (KPIs): - Ratio of inbound users of the network by 10% (effectiveness of the network to inbound tourists who demand connectivity to the Internet) - In-town communications and information sharing without the use of the Internet assuming loss of Internet connectivity due to disasters - Characteristics of users about tourism Measurement Methods: - Analyzing access logs and users' answers to a questionnaire by us Standards/Interoperability: - NerveNet utilizes standard LAN and IP protocols and systems. Any network appliances with Wi-Fi or LAN interfaces can be connected to it. It provides transparent connection to the Internet. Replicability, Scalability, and Sustainability: - NerveNet is ready for commercial use and industrial members of the team are ready for business partnership. Impacts: - Economic growth by increased number of tourists visiting the town in safety - New jobs by increased number of companies moving into the town because of the resilient town network Demonstration/Deployment Phases: Phase I Pilot/Demonstration June 2016: The pilot system of NerveNet was installed in Shirahama town May 2015 and has been operated. Since nearly six thousand tourists and residents have used the network, the town office recognized it to be necessary and determined to allocate the budget to maintain and expand it. Demonstration with a small set of the system is possible at the Expo. Phase II Deployment June 2017: The capability of information sharing in emergency situations would be increased. Expansion and enhancement such as connecting sensors and digital signage would be realized.
Description: ・A fusion of the phased array weather radar data and the utilization of large-size social data, “Big Data” ・Real time alert display and mail delivery system for the localized torrential rainfall Challenges and Solutions: ・A localized torrential rainfall is one of the causes of recent urban disasters in Japan. But it is quite difficult to predict accurately because it happens suddenly within a small area. ・To solve this problem, we are developing a phased array weather radar with which we can obtain real time 3D data of the rainfall, and also developing a real time alert display and mail delivery system. Major Requirements: 1. Three-dimensional rainfall observation system (weather radar) 2. Correct real time three-dimensional rainfall data 3. Real time processing for the early detection of the localized torrential rainfall within a minute. 4. Integrating the early detection of the localized torrential and the local static hazard map 5. Processing the alert level (CAUTION and ALERT) 6. Display and mail deliver of the alert level for administrative officer Performance Targets/ Key Performance Indicators (KPIs): ・Accuracy rate of alert is more than 80% ・Accuracy rate of caution is more than 60% Measurement Methods: ・Comparison between the predicted early detection area and actual rainfall rate Standards/Interoperability: ・Three-dimensional rainfall observation Impacts: ・Reduce the flood damage Demonstration/Deployment Phases: Phase I Pilot/Demonstration June 2016: ・Enhance the accuracy of prediction ・Demonstration test in Kobe city Phase II Deployment June 2017: ・Enhance the system liability (combined with Big Data)
Brief Description: • ROSE project is based on the integration and development of advanced ICT tools that can provide the coordinated work of customers, aggregator and Distribution System Operators (DSO). • ROSE project is the support for DSOs and customers to plan and adapt the energy consumptions to the best situation, usually looking for cheaper costs. Challenges and Solutions: • ROSE project is the technical and economic viability of intelligent Smart Microgrid nodes, interconnected with Smart Aggregators for global optimization as an effective way to implement an open, active demand/response system integrated with the Grid. • The result of ROSE project is a platform integrated with Smart Aggregator and the DSO to send the D/R signals to customers. • ROSE project is a new paradigm of heterogeneous systems interoperability with Smart Aggregator component based on Real Time Semantic Engine, fed by endogenous data grid and web&social networkl source appropriately distilled Major Requirements: • Innovative ICT technologies • Testing and development of simulation and optimization models within Energy Management System for monitoring, planning and management of energy systems • Improvement of economic and environmental sustainability Performance Targets/ Key Performance Indicators (KPIs): • Day-ahead production scheduling of dispatchable sources and storage exploiting renewables forecast and optimization techniques • Real time optimal control of production and storage systems • Optimal thermal & electrical energy consumptions, minimizing the CO2 emissions, annual operating costs and primary energy use • Actually the status of the project is at concept level, shared and approved by Municipality and University of Genova then the goal is to obtain the following KPI: overall usage of power generated by renewable sources in the Microgrid (target: 25% increase), reduction of CO2 emission (target: 10% reduction) Measurement Methods: • Benchmarking based on historical data and on power plants data; periodical measurements of energy produced and either stored or sent to the grid; estimates of CO2 overall reduction of emissions based on the benchmarks Standards/Interoperability: • The relevant ICT component of ROSE project is Smart Aggregator. • Smart Aggregator is a data platform with a fully-configurable Semantic Engine to analyze, measure and evaluate Big Data in Real Time • Smart Aggregator has a complete suite of synchronous and asynchronous API for integration with existing enterprise platforms (e.g., Operational Intelligence, Business Intelligence, etc.). Replicability, Scalability, and Sustainability: • The Smart Aggregator is a fully software solution that can be deployed either on-premise or in the cloud. As such is fully replicable. Scalability is ensured by the software architecture itself that is a derivation of a well-established web listening solution of MAPS (WebDistilled) that already handles at more than 4Million events per day. Sustainability is also ensured by the immateriality of the solution that can be replicated with a minimal environmental impact Impacts: ROSE project optimize smart grids within three different levels: 1. Micro-Grid/Smart-Grid a. Data from Microgrid Operational Management b. Data from Demand/Response Productive building c. Data from Planning and Forecast 2. Smart Aggregator 3. DSO (Distribution System Operators) a. Decision requirements b. Market information Demonstration/Deployment Phases: Phase I Pilot/Demonstration June 2016: • Concept and Solution Architecture Presentation • Real Time Operational Intelligence with Smart Aggregation Demo Phase II Deployment June 2017: • Pilot Project in collaboration with Municipality of Genova - Italy Team Lead: • Mr. Giuseppe Franceschelli email: [email protected]
Description: This project will create efficiencies that will enable Lindale and other similar cities to enhance their patron’s experience when visiting their developments. In addition, it will provide needed analytics to assist in measuring the success of their mixed use developments. Once implemented, we will converge smart technologies (Wi-Fi, AMI, Video Surveillance, Smart Lighting, Traffic, Parking etc.) into a single “Pane of Glass” which will allow for Big Data Functions such as analytics, predictive analytics and KPI tracking and centralized oversight. o Reduce need for human oversight. PD, FD, PW while increasing efficiency of these functions o Allow for informed decisions as it relates to use/acquisition and use of human, physical and marketing capital. o Making the data available to businesses, entrepreneurs, and public. (Free and Paid) Challenges and Solutions: • Access to development and to venues - predicting influx of visitors, managing traffic, wait times etc. – Video analytics, Verizon Traffic and Parking • Relevance to Millennials – Music and technology integration. Including WiFi, Social Media, streaming • Inefficient City Services and Cost – Use sensor, remote monitoring and data analytics to improve efficiency and reduce cost of city services. • Limited local businesses promotion – Allow businesses to electronically advertise on kiosks. • Funding - Generate revenue via business advertisements. Digital signage/Kiosks, Social Media • Safety and Security – Ensure safety and feeling of safety – Intelligent Lighting, Video, Call boxes, Digital Signage, Wayfinding Major Requirements: • Develop and assemble project team • Gain stakeholder support and buy-in from the community and run pilot Create scope and requirements, project plan o Prioritize and match to budget • Fully define Phase I and II implementations o Specify quantity, capabilities o Establish benchmarks • Implement Phase I Technologies o Identify funding o Recruit tenants o Assemble partner team o Implement Phase 1 technologies • Implement Data Analytics Platform • Water • Lighting • Video • Traffic / Parking o Measure results/compare to benchmarks • Implement Phase II o Evaluate analytics for expansion and optimization. o Use data to determine placement of Digital Signage Performance Targets/ Key Performance Indicators (KPIs): Increase by event attendance: +30% Increase Sales Tax Revenue: +50% Water dept man hours -50% Parking Search Time: -40% Event Staff: -20% per capita attending events Vehicle traffic wait times: -10% Increase in Property Values +10% Measurement Methods: • We are going to measure the above based on benchmarks established from data collected during Phase I and manually collected data from 2015 events. Standards/Interoperability: This project will leverage a data analytics platform as the single “Pane of Glass”. This platform will have a distributed architecture, integrated development and deployment features, and native security and data-aware operations reduce application development time while providing Enterprise-Grade, non-stop operations. The data analytics platform we select will enterprise grade security based on RSA WS-Security for SOAP and https for REST web-services. It operates with external Directories through LDAP to deliver identity management. Business rules are established using WS-BPEL compliant business rules engine and Web Services SDK. Cloud Services provided by Verizon and other service providers will connect to the platform via API’s for data extraction and import to the analytics engine. Infrastructure services will all be standards based: • GPS – NMEA • Landline – IP, Fiber, Ethernet • Wireless – 802.11 • Cellular – 4GLTE, 3GPP • Standards based Encryption Replicability, Scalability, and Sustainability:. • Replicability: o Easily replicable. Data Analytics Platform, Verizon and other partners have representation nationwide and some globally o Platform as a service reduces dependence on infrastructure o Applicable to a large or small development or large city • Scalability: o Cloud based architectures and underlying software are dynamically kept current. Storage, Memory, performance all expandable o Most solutions mobile making it easy to expand as we grow or relocate assets like cameras etc. • Sustainability: o Increased tax revenues will fund expansion and growth. o Solid/Stable technology partners o Solid and Stable private partners o Adds little if any additional burden on city staff. • Security elements act as force multiplier for Public Safety. o Flexible interface can connect to over 40+ protocols o Solar incorporated into some solutions o Music in Texas is here to stay. Project Impacts: • Increase in Tax Value of Lindale downtown and other areas of the city. • Attract new businesses to the area • Expand Lindale’s presence in the education space, TJC. • Retain mellinnials • Provide a safe easily accessible destination for visitors and surrounding communities • Minimize impact on city services through implementation of key technologies • Provide an immersive media experience from vehicle to event. • Increase citizen and business involvement by making data available. Demonstration/Deployment Phases: Phase I Pilot/Demonstration June 2016: • Data Analytics Platform • Fleet • Water • Lighting • Surveillance Phase II Deployment June 2017: • Predictive traffic Analytics • Parking • Digital Signage/Kiosks o Parking o Public Info o Public safety • Social Media • Retail Specific enhancements
Description: Our second autonomous vehicle pilot will build upon the “lessons learned” from our GCTC 2015 “First Mile/Last Mile” study (GCTC Action Cluster SMOOTH). The City of Columbus was recently named one of the seven finalists in the US Department of Transportation Smart City Challenge. Our GCTC 2016 project will, therefore, concentrate on a scalable and replicable low speed automated shuttle solution for use in the Smart City of Columbus. This automated shuttle solution will use a small (two-seater) electric driverless vehicle with a scalable and replicable software, hardware control and decision making architecture. The eventual aim of the project is pilot deployment in an urban driving environment with low speed vehicles and intersections at/near the outdoor shopping area of Easton Town Center in Columbus. The scalable and replicable approach will enable the easy adaptation of the same system to other parts of the City of Columbus and to other similar pilot deployment sites in other cities in the US. Challenges: The City of Columbus is a typical mid-sized city in the U.S. with a steadily growing population. Indeed, the population of Central Ohio where Columbus is located is projected to increase by over 500,000 until 2050. Planning and developing a smart regional transportation system is an important challenge and issue to be addressed. Columbus does have a bus system but it is not easily accessible especially by the people who need it most due to the first-mile and last-mile problem. Being one of the seven finalists in the U.S. Department of Transportation Smart City Challenge, the City of Columbus has identified the use of automated electric shuttles as a potential solution to this challenge. The use of electric shuttles will also introduce a beneficial environmental footprint. The SmartShuttle project is on the development and use of low speed automated electric shuttles in a typical deployment site, the Easton Town Center outdoor shopping area. It is expected that the SmartShuttle concept will be easily scaled and replicated for use in other deployment sites in the city and in other cities. Major Requirements: • Develop technical expertise • Build relationships • Address state legislation • Address local legislation • Do proof-of-concept demo • Scale and replicate for other deployments We will continue to develop the technical expertise and build the required relationships/partnerships with the private sector, at OSU, other academic and research entities, and with state and federal organizations. New legislation allowing testing of autonomous vehicles with manufacturer license plates has been accepted in Ohio. We will use it for pilot deployments and implementations within Columbus. We estimate a base budget for the SmartShuttle proof-of- concept” pilot deployment at $300,000 to $400,000 with a cost-sharing approach between government and industry. If we are awarded the USDOT $40M “Smart City Challenge” we may extend the proof-of-concept testing in Easton Town Center to an actual deployment, with deployments in other parts of the city to follow. Performance Targets/ Key Performance Indicators (KPIs): Improvements will be calculated on a per smart shuttle basis and will be extrapolated based on the number of vehicles planned in actual deployments. A 20% improvement in the traffic jams in the Easton Town Center area and other SmartShuttle deployment sites as the automated electric vehicles will replace a certain portion of road traffic. A 50% improvement in solving the first-mile and last-mile problem in the deployment sites. A 20% reduction in air pollution due to traffic in the deployment sites. Measurement Methods: The traffic jam improvement will be determined and extrapolated for a larger deployment. The number of people in bus stops using the on-demand automated shuttles will be recorded. The tons of CO2 reduction based on reduced emissions from drive alone vehicles replaced by the electric shuttles will be used for air pollution reduction computation. Standards/Interoperability: There are currently no established standards especially for low speed automated shuttles. Interoperability of shuttles from different vendors using different automation and operation architectures is a serious concern. We will develop a unified and hence interoperable architecture for this purpose. An NSF EAGER project for the NIST GCTC call has been proposed for this purpose. Replicability, Scalability, and Sustainability: The automated shuttles used will have a scalable and unified automation solution, making the results easily transferrable to other vehicle types and other pilot deployment. This will enable the scaling and replication of the automated shuttle solution in Easton Town Center to other parts of Columbus (downtown area, OSU campus) and to other cities. Project Impacts: We will be providing a full mobility solution to people who could not easily commute to work due to the first-mile, last-mile problem increasing their chances of getting a job. There will be a reduction in traffic jams, which will increase the quality of life of those people who are affected by it. There will be an improvement in air quality and heavily populated area due to the use of electric vehicles. Columbus and Ohio will experience economic growth due to the new jobs created by the automated shuttle industry including development, operation and maintenance. Demonstration/Deployment Phases: Phase I Demonstration June 2016: The demonstration in June 2016 will use a street legal and automated two seat neighborhood electric vehicle. This vehicle is already equipped with 4G connectivity by Verizon. This demo will show its architecture and its automated driving capabilities. Phase II Demonstration June 2017: The aim of the June 2017 proof-of-concept demo is to use the same automated neighborhood electric vehicle in the Easton Town Center outdoor shopping area within a mixed traffic environment with other vehicles and pedestrians. Success of the Smart City Challenge application of the City of Columbus will have an important impact on this second demo as the Easton Town Center will have a fleet of autonomous electric vehicles operating in a loop in that case. This will ease the demo deployment which is aimed at the inner loop in the Easton Town Center area. The City of Portland is also a Smart City Challenge finalist. If the City of Portland is successful in its Smart City Challenge proposal, the results will be transferred to a chosen site in Portland. The cities of Greenville, Boston and Washington D.C. are also interested in deploying the results of the SmartShuttle technical cluster and will have the chance to do so by working with the cluster leads and the manufacturer of the automated vehicle.
Description: Our second autonomous vehicle pilot will build upon the “lessons learned” from our 2015 “First Mile/Last Mile” study and will have (a) a demonstration using a street legal neighborhood electric vehicle with on-demand ordering capability, (b) a pilot operation in a chosen pedestrian area on the OSU main campus, (c) demonstration of socially acceptable collision avoidance Challenges: The population of Central Ohio is projected to increase by over 500,000 by 2050. Planning and developing a smart regional transportation system is an important challenge and issue to be addressed. The Ohio State University campus is an excellent testbed to try new modes of transportation like on-demand automated shuttles. These on-demand automated shuttles will also work in pedestrian zones in campuses like the Ohio State University campus. Automated shuttles operating close to large pedestrian groups creates the important problem of socially acceptable collision avoidance with pedestrian groups. Major Requirements: We will continue to develop the technical expertise and build the required relationships/partnerships with the private sector, at OSU, other academic and research entities, and with state and federal organizations. We will also sponsor legislation that will be necessary for future pilots and implementations to occur beyond the Ohio State University core campus. We estimate a base budget for the SMOOTH(2) “Proof of Concept” pilot at $300,000 to $400,000 with a cost-sharing approach between government and industry. If we are awarded the USDOT $40M “Smart City Challenge” we may increase the scope of the pilot deployment in the Ohio State University campus. Performance Targets/ Key Performance Indicators (KPIs): A 20% increase in use of automated electric vehicles in transportation and a reduction of CO2 tons of emissions. Calculations will be made based on one electric vehicle we automate and will use to replace a fossil fuel powered vehicle. This impact will be extrapolated to the number of automated electric vehicles that the City of Columbus plans to implement in its Smart City Challenge proposal plan. Measurement Methods: Measurement will be based on the usage of a fossil fueled vehicle in the OSU campus route(s) chosen for the pilot test. Standards/Interoperability: We will be compatible with the National Architecture and interconnect to multiple transportation venues accordingly. Replicability, Scalability, and Sustainability: Our solution will be based on model based design for ease of replicability, scalability and sustainability. Project Impacts: Safely deploying electric, autonomous vehicles will have a significant impact on lowering CO2 emissions and radically transform the global transportation system. We will be providing a first-mile and last-mile solution to the residents of the Ohio State University campus (replicable in the city and elsewhere). Demonstration/Deployment Phases: Phase I Pilot/Demonstration June 2016: A proof-of-concept AV demo in the Ohio State University campus is planned. New legislation allowing autonomous vehicle testing in the state of Ohio has passed. We are working on how it will affect university campus deployments as the university is not a manufacturer. Phase II Pilot/Demonstration June 2017: A proof-of-concept demo deployment in a pedestrian only zone of the Ohio State University campus is planned. Socially acceptable collision avoidance will be demonstrated.
Description: Set-up an IoT tracking system to effectively identify Internally Displaced Persons in Taraba, starting from the Point of Conflict. 1. Ascertain how they currently survive and identify ways to remedy their suffering by making basic amenities available to them. 2. Ensure that the aids given to them from various sources eventually reach them and are properly utilized by them. Challenges: 1. With daily influx of IDPs from local governments and neighboring states, it will not be easy to get the exact number of IDPs without proper systems in place. 2. Mobile networks is not yet available, and need to be in every part of Taraba state where people currently live, for the system to work effectively. 3. Funding is needed to acquire a gadgets and technology that will help us put the system in place. Major Requirements: 1. Since kidnapping and other internal conflicts like the activities of Fulani herdsman is becoming a daily occurrence, we will setup a cloud based app to deploy satellite resources to an area of conflict. 2. People will need to text a code to an app when they notice any security breach. The already setup satellite resources will then be triggered to automatically deploy technologies like google earth to take snapshots, and videos of the scene of conflict. 3. The cloud based program should accept various kinds of data about the area of conflict and IDPs as they are being displaced. 4. After that, the real life captured information should be instantly sent to personnel and relevant authorities who will swing into action to monitor the internally displaced. 5. Government personnel like Police, NEMA, government agencies and International NGOs working with IDPs will need to be trained on how to use the data they will receive from our cloud based IoT program. 6. We will get agents that will train people on how the technology works, so that they can use it for their safety. Performance Targets/ Key Performance Indicators (KPIs): 1. By July 2016, pilot of the cloud based application should have been setup by 50%. 2. By December, 2016, 90% of all parts of Taraba should have been connected to mobile networks which is necessary for the technology to work effectively. 3. By March, 2017, 99% of Tarabans should have understood how to use the IoT based technology to send information. 4. By June 2017, (over 90%) of IDPs and all bodies concerned with IDPs and Security should be comfortably using the technology. Measurement Methods:. 1. Data collected with our technologies will be compared to data already on ground. 2. Data will also be compared to industry standards of data manipulation systems in place. Standards/Interoperability: It will use cloud based technologies, internet connectivity and mobile apps together with IBM’s IoT platform for integration and for developing connected applications. Replicability, Scalability, and Sustainability: The project can be easily replicated and customized for use in other local governments across the state, and states in North Eastern Nigeria where insurgency is heavily pronounced and there is a high incidence of IDPs. Project Impacts: Security will be checked, peace will also be enjoyed as new influx of people to Taraba has been a major cause of communal and land clashes lately. 1. Activities of managers who siphon help meant for the over 45,000 IDPs on record; to other uses will be checked. Help will finally reach IDPs as it should and more lives would be transformed. 2. Jobs will be provided for agents who will work with IDPs. 3. Foreign donors will be confident to send in help since they will have access to data that will help them know their help is used as it was meant to be used. Demonstration/Deployment Phases: Phase I Pilot/Demonstration August 2016: A prototype of the cloud based program and mobile app must have been created and ready for testing on IDPs. Phase II Deployment June 2017 IDP records must have been collected and the data used to solve their problems.
Description: OpenMove is a software solution for smart mobility that allows to create, edit and sell digital tickets of transport and parking via app or webapp. Transport companies may even import open data for transportation (GTFS), which is immediately converted in actual tickets. OpenMove: 1) is the only plug&play platform: transport companies set up autonomously an entire mobile ticketing solution with no effort and no need of IT capabilities; 2) is compatible with all means of transport and parking; 3) is “as-a-Service” solution with plain business model: no initial costs, no hardware, just 5% fees. Challenges: Transport companies don’t have a digital sale channel at their grasp (like hotels do: booking.com; musicians do: iTunes; private drivers do: Blablacar). This is a big pain particularly for small and medium companies because they are unable to implement and maintain a proprietary system. OpenMove literally breaks entry barriers offering a ready-to-use turnkey solution, taking away technological and managing effort. OpenMove is made of: - App for users. Users find and pay tickets for transport and parking. - Admin platform for transport and parking companies. They simply sign up and are able to create, edit and push tickets on the smartphone app. - App for ticket inspectors, to check the validity of tickets. Major Requirements: OpenMove is available as a commercial solution since March 2015, having a significant reference case in Province of Trento (Italy), where it manages mobile ticketing for the entire public transportation. Starting from this living lab, the goal is now to reach US market. • Make contacts with the open data community in US and with Fiware community, for networking and dissemination purposes. • Showcase OpenMove solution and find partner cities or transport companies that want to use our mobile ticketing solution. • Understand needs by stakeholders in US (cities representatives, municipalities, transport companies) and explore the local scene. • Deploy OpenMove in concrete scenarios, tailoring it to aforementioned needs to set up significant use cases and contribute with tangible impact. Performance Targets/ Key Performance Indicators (KPIs): • 10% of tickets sold are going to be paperless with 12 months • 90% retention of users who try mobile ticketing and abandon paper ticketing • 380Kg CO2 saved and 1.35Kg paper saved every 1.000 digital bus and train tickets Measurement Methods: • Number of users and tickets sold compared to actual scenario. Standards/Interoperability: This project will leverage on FIWARE (fiware.org), a public, royalty-free and open source platform that eases the development of Smart Applications in multiple vertical sectors. Besides being one of the reference platforms for GCTC 2016, FIWARE is contributing to the International Technical Working Group on IoT-Enabled Smart City Framework launched by NIST. FIWARE brings the NGSI standard API which represents a pivot point for Interoperability and Portability of smart city applications and services. This project will also make use of OGC standards (Open Geospatial Consortium), to access to open geospatial information offered by the SDI of the cities. Replicability, Scalability, and Sustainability: Such FIWARE NGSI API is one of the pillars of the Open & Agile Smart Cities initiative (oascities.org), a driven-by-implementation initiative that works to address the needs from the cities avoiding vendor lock-in, comparability to benchmark performance, and easy sharing of best practices. There are currently 89 cities from 19 countries in Europe, Latin America and Asia-Pacific who have officially joined this initiative, including the city of Valencia. Economic impact: transport companies get an added sale channel, save cost (no setup fees, no proprietary servers, no maintenance, no hardware required, no personnel costs) and benefit of improved decision making (deployment in record times, no effort on their side, no IT skills required). Social impact: OpenMove is an application tailored for the smart society: citizens and tourists are enabled to find the right ticket anywhere and anytime. They save money and time, having no distress of reaching the ticket shop or currency and language issues. Environmental impact: People easily access to public transport and embrace multimodality, benefitting of complementary means of transport. Fostering public transport yields to reduced CO2 emissions and digital tickets help to save paper. Demonstration/Deployment Phases: Phase I Pilot/Demonstration June 2016: • Showcase the reference case in Province of Trento • App, admin platform and app for inspectors are on the market • Prototype of plug&play platform (to be used autonomously by transport companies and municipalities) is available Phase II Deployment June 2017: • OpenMove is up and running in some cities in US • Plug&play platform is in production
Description: • Deploy software-defined cloud-driven wireless sensor networks for flexible monitoring of diverse underground infrastructure components, including manhole-cover fidelity, toxic gas levels and floodwater in tunnels, theft/destruction of communications equipment, and eventually water- and power- distribution infrastructure in the project cities. • Develop the planning and decision-support capabilities necessary to provide city government officials with real-time situational awareness of underground assets, while maintaining cost- and power- efficient operation of the sensor network. Challenges: • The underground environment is harsh and variable, which makes it difficult to consistently maintain wireless connectivity, and also to efficiently deploy and manage sensor nodes. • The networks will have many nodes with diverse functions and accessibility requirements (for instance, already 1200 sensors have been installed to monitor manhole covers in just one neighborhood in Beijing). Operating the network in a reliable and cost-effective manner, while also providing adequate observability of infrastructure health, is a challenge. • Algorithms are needed that detect and localize failures/threats from sensor data, and adapt sensing or support deployment of control resources when threats are detected. Major Requirements: 1) Following on an initial deployment of 1200 manhole-cover sensors in Beijing, the project will pursue deployment of: a) man-hole cover sensors in other neighborhoods and cities, b) other tunnel sensors (e.g., for detecting cable theft/destruction, floodwaters, gas, etc.). 2) Adaptive wireless node management algorithms will be developed, which improve operational efficiency in the harsh underground environment (higher-fidelity transmission, lower power usage). 3) Sensor placement and sensor-network management algorithms will be developed, that permit efficient deployment and recruitment/use of sensors for wide-area observability of infrastructure health. 4) Alternative technologies, such as distributed software-based solutions rather than cloud-based solutions (using more sophisticated microcontrollers at repeaters and nodes), will be explored to enable efficient network management and data processing. 5) Threat-assessment algorithms and software will be developed, which process the high-dimensional data streams from the sensors to give situational awareness about emerging concerns, and alert appropriate authorities about the concerns. 6) Monitoring of water-distribution networks will also be pursued in a preliminary way. Specifically, the possibility for using sparse sensing together with models of water network to identify threats will be studied using formal techniques. Subject to support from governmental partners, deployment of sensors for water-system monitoring will also be pursued. Performance Targets/ Key Performance Indicators (KPIs): The success of the project is defined by the ability to identify low probability high-impact anomalies in the underground infrastructure, so as to prevent catastrophic impacts (e.g., flooding of roads and walkways, pedestrian falling through manhole cover, health impact to underground workers due to toxic gas, contamination and deliberate threats to water sources) and enable low-cost resolution of hard-to-reach hazards (e.g., replacing underground cables that have been stolen or damaged). Thus, a KPI for the project is the number and diversity of anomalies identified. In turn, the project will help city governments to avoid costly repairs and reduce manual maintenance programs, as measured in saved financial costs (hundreds of thousands of dollars) and man-hours of work (from hours/days to minutes) per event. Another KPI is lives saved from manhole accidents and flash floods, which are much publicized in China. Measurement Methods: The number and diversity of anomalies identified will be a direct outcome of the threat-assessment software. For example, each time a manhole cover is lifted – whether for theft or for legitimate access by workers – we will record it in the database. Thus we will know how many times it occurs. This will allow placement of safety measures around the manhole cover. Water level data will be recorded, so we will know which areas get a lot of water (i.e. water rising above manholes), and which do not. This tells the city where to improve drainage. All these data will be recorded and can be looked at / compared over time. For quantitative cost-saving metrics, we will communicate with government officials and contractors about expenses avoided for the identified alert events. Standards/Interoperability: Currently we are using proprietary software-defined cloud-driven wireless sensor network, where all the intelligence happen in the cloud software. For next generation, we are looking at standards based architecture. Specifically, LoRa is currently being evaluated as a possibility. However, LoRa only supports one-hop network, which is not enough to get to the nodes in the tunnel, so we are looking at adding battery-powered multi-hop to LoRa to enable communication from inside the tunnel to the repeaters outside. We are considering adding this as an extension to the LoRaWan standard. Tradeoffs between the proprietary solution and the standards-based ones will be explored in the project. Replicability, Scalability, and Sustainability: Monitoring of underground infrastructure requires large-scale sensor deployment on heterogeneous resources, and at the same time must be highly cost efficient to be appealing. Thus, scalability and sustainability are key project goals. The project will use networking technologies (software-defined wireless networking, distributed software, etc.) and adaptive algorithms to support scalability and sustainability. Regarding replicability, underground-infrastructure monitoring needs are common to most large cities, and we expect the developed technologies to be implemented in multiple cities. Project Impacts: The project will enable cost-effective monitoring of diverse underground infrastructures in a city, which are vital to day-to-day lives of residents. Thus, the project will provide significant benefit to city governments and residents in terms of safety, cost to monitor and address failures and other threats, and seamless operation of city services. The project will also lead to new scientific insights into threat monitoring and management in large-scale legacy infrastructures, using software-defined wireless sensing technologies and mission-adaptive algorithms. Demonstration/Deployment Phases: Phase I Pilot/Demonstration June 2016: • Display of data from initial deployed network (1200 manhole covers), and visualization/manipulation of the network via remote access to the cloud (already done). • Demonstration of wireless-node power-management algorithms, to enable higher-fidelity operation underground with low power usage. • Preliminary demonstration of adaptive monitoring and anomaly detection from the sensor network. Phase II Deployment June 2017: • Comprehensive deployment of sensors for manhole covers, tunnel flooding and gases, and underground equipment, in multiple Beijing neighborhoods. • Deployment of a full algorithm suite to support adaptive wireless node and network management, and threat monitoring. • Preliminary studies on water distribution system monitoring.
Brief Description: • Next Gen communications/networking for delivery of hyper-local, user driven, context aware severe weather warnings. • Mobile phones and hyper-local data enable customization to improve response and outcomes • Development of communication, networking and warning concepts benefits from live experimentation and user co-creation • CASA has established a Living Lab for Severe Weather Warning with an end-to-end warning infrastructure from radars to the public. (http://www.openlivinglabs.eu/livinglab/casa-dallasft-worth-living-lab-severe-weather) Cities are facing greater vulnerability due to increasing population concentration and frequency/severity of storms Challenges: • Affordable, high-bandwidth uplinks for high resolution radars • Infrastructure failures during severe weather events • Prioritization of warning information delivery based on socio-environmental risk • Provision of warning information to individuals in vehicles • Provision of warning information that triggers appropriate user behavior Major Requirements: • Build a weather warning system that ingests information from sensors and forecasts • Build a smartphone app that enables targeted alerts based on user context • Create models for the implementation of (radar) sensor networks for public safety and economic benefit • Design these networks based on new cloud computing and software defined networking technologies • Create a “plug and play” platform for technology innovations Evaluate system with real weather and real users • Evaluate how SDX/SDI can support this system Performance Targets/ Key Performance Indicators (KPIs): • Instant delivery of warnings (< 2 minutes) of strong winds, tornadoes and heavy precipitation events to the public to protect lives and property • 100% availability of radar network and warning communications infrastructure • Acceptance of system and information generated by system by National Weather Service and Emergency Managers • Measurement Methods: • Simulation/measurement studies to test communications/networking concepts • User surveys and focus groups to determine acceptance and effectiveness of warning communications Evaluation of warning behaviors through tracking app data. Standards/Interoperability:. • Establish new standards for prioritized communication of weather warnings • Establish common language for communication of high precision warnings in conjunction with NWS, Emergency Managers, and the general public Replicability, Scalability, and Sustainability: Describe how the project could ensure replicability, scalability, and sustainability of the operation. • Engagement of major vendors (radar manufacturers) and National Weather Service in the project to establish common standards. • The CASA Urban Demonstration Testbed in the Dallas/Fort Worth Metroplex could be seen as a model for other major US cities Project Impacts: This project has the potential to save lives and property in the case of severe weather events through the delivery of geographically targeted, user defined alerts to users on mobile phones through custom designed app. This system will provide essential information to mobile users in severe weather events based on context. Demonstration/Deployment Phases: Phase I Pilot/Demonstration June 2016: • Focus groups and surveys on public to determine prioritized warning delivery and messages. • Evaluations of socio-technical risk. • Demonstration of operations during past severe weather events in DFW. Phase II Deployment June 2017: Deployment of communications/networked system in Dallas Metroplex leveraging DFW Living lab infrastructure of 8 networked radars, that produce severe weather warnings on mobile phones of participating individuals (200+ general public participants, 20-50 Emergency managers, private sector evaluators from local airports, hospitals) and on systems used by the National Weather Service.
Description: LinkNYC is a first-of-its-kind communications network that will bring the fastest available municipal Wi-Fi to millions of New Yorkers, small businesses, and visitors. The five-borough LinkNYC network, which will be funded through advertising revenues, will be built at no cost to taxpayers and will generate more than $500 million in revenue for the City over the first 12 years. The approach used for this program was to bring the best companies together that are subject matter experts in their respective areas to deliver a product that would provide a public services to citizens and generate a revenue stream for the City of New York. Partners include New York City, Qualcomm Incorporated, Intersection, and CiviQ Smartscapes. Challenges: The aging network of public pay telephones for years have been a less than utilized form of communication that were not generating revenues for the city, as well as an eyesore on the community. The challenge of this project was to design, manufacture, install, and operate a state of the art networked communication system that will bring the latest technology to bear to enrich the lives of New Yorkers and visitors from around the world and provide the fastest free Wi-Fi connectivity for free. Major Requirements: • Identify Overall customer use cases to meet NYC requirements and provide the best user experience to NYC citizens and visitors • Identify key partners to support the manufacturing and deployment of structures and associated services bringing jobs and innovation to NYC. • Work with NYC to schedule pilot structure and testing in New York -- completed • Plan commercial launch by late 2015 -- completed • Leverage key learning's to develop a repeatable deployment model for other cities. Performance Targets/ Key Performance Indicators (KPIs): • Rigorous deployment schedule of 7,500 Links • Increase internet connectivity to the 730,000+ (~27%) New Yorkers that do not have internet in the home. • Measure usage statistics of the network to ensure increasingly “Bridging the Digital Divide” for New Yorkers who do not currently have internet connectivity • Subscription Numbers • Session Growth • Data consumed by network by location/neighborhood • Broad usage of the network by all ages, languages and device types (Android, Windows, iOS, etc.) • Provide $500M+ revenue to the City of New York Measurement Methods: • Weekly tracking of Link deployments (installed, WiFi enabled, power enabled) • Daily monitoring of usage statistics to evaluate use and health of the network • Monitor usage location to ensure increasing internet connectivity throughout the 5 Burroughs. • Tracking of statistics on the network by age and language of users to provide support and enhancements for the citizens of NYC. Standards/Interoperability: • Using open, widely used IEEE 802.11 WiFi standards that are interoperable with other devices/sensors but also compatible with all WiFi enabled smartphones/tablets/computers. • Pass point Hot Spot 2.0 allows roaming between Links without disengaging from the network • USB Charging Impacts: • Improve street side appearance with a state of the design and technology. • 911 and 311 access for public information and safety. • Improving Socio-economic parity for all residents and businesses. • Improved quality of life for NYC residents and visitors via free internet access and state of the art Wi-Fi service. • Bridge the digital divide and bring free internet access to underserved communities • A facility for location manufacturing and production will be established in NYC for the LinkNYC structures. • Creation of 100 to 150 new full-time jobs in manufacturing, technology and advertising. • An estimated 650 support jobs in NYC. • A new revenue stream for NYC. • Sleek design uses smaller footprint restoring sidewalk space previously used by large payphone enclosures • ADA Compliant Demonstration/Deployment Phases: Phase I Pilot/Demonstration July 2016: • Minimum 500 deployed Links by June 2016 • WiFi connectivity availability • 911 Calling enabled • 311 Services enabled • Internet Browsing • Free phone calls in the United States • Public Service Announcements pushed to Links throughout the city Phase II Deployment: • At least 510 gigabit Links will be installed across all 5 boroughs by July 2016. • Based on current fiber buildout and technical viability, we expect to deploy the first 510 Links in the following areas over the next 7 months: • 3rd Ave and 8th Ave above 14th Street, Manhattan • • Northern Manhattan • South Bronx • Jamaica, Queens • Flatbush Ave, Brooklyn • St. George, Staten Island • • Within the first 4 years, at least 4,550 Links will be installed, and every one of them in Brooklyn, the Bronx, and Queens will have gigabit speed. • We will release deployment information to the public on a rolling basis and will announce all new locations in advance.
Description: In 2015, Seoul designated the Bukchon area which is comprised of closely-situated traditional houses, museums and restaurants as an IoT pilot zone. Seoul only provides vital infrastructures such as free Wi-Fi, sensors, contents in foreign languages and open API so the private sector can develop IoT services by using the infra, test out their new services and make profit while alleviating the resultant urban issues in Bukchon. Challenges: Difficulties in creating and adopting a standardized IoT platform - IoT technology is in the early stage that there is no standardized platform yet. We adopted the common IoT platform developed by the central government, and we are now accelerating the platform to be interoperable with other private IoT platform. High cost -IoT technology is changing and evolving fast that it is costly to employ. Major Requirements: Designate Bukchon as an IoT pilot zone to develop services that resolve urban issues of Bukchon Identify problems and find a direction of the project with residents of Bukchon: In-depth discussion among citizen, Bukchon Open Forum, ISP(Information Strategic Planning) on Bukchon IoT project, etc. Examine business models with the private sector and provide supports that small & mid-sized companies need to develop urban problem solving IoT services in Bukchon. Establish vital infrastructure for IoT services to be implemented by the private sector Expand the IoT project to the entire Seoul by 2020 Key Performance Indicators (KPIs) To create a digital Seoul city where urban spaces and digital spaces are connected by IoT technology To resolve urban issues in two major areas; safety and tourism Measurement Methods: Seoul is in the process of developing indicators to measure the impact and effectiveness of this project. Standards/Interoperability: Establishes vital infrastructure such as free Wi-Fi, open API, contents and sensors that are available to apply and demonstrate private IoT services and opening it to the public (It is difficult to attract investors for sensor-based O2O services because it requires costly infrastructure. Therefore, Seoul turned the Bukchon area into an IoT test bed equipped with sensor-based services) Replicability, Scalability, and Sustainability: This project will be replicated to the entire Seoul by 2020. Since the Seoul Metropolitan Government won’t be involved in the area where private sector can make profits and only focus on developing indispensable infrastructure, it’s a good model for sustainable public-private partnership. Project Impacts: Decrease in in conveniences for residents of Bukchon - With the continuous increase of tourists, diverse urban problems have been arising including trash, noise, parking and trespassing in Bukchon. However, after the launch of the project, many IT companies launched IoT services such as parking lot sharing system, smart garbage bins, and smart disaster prevention system by using the infrastructure provided by the city and they are alleviating the resultant urban issues. Open test bed for companies - Companies can test out their new IoT services or products in Bukchon and improve them before launching them to the market. Improve the quality of sightseeing experience for tourists - Development of location guide apps, audio service, information service for amenities, etc Demonstration: Phase I Pilot/Demonstration June 2016: -Expand the IoT infrastructures -Accelerate the IoT platform -Create and operate an IoT living lab Phase II Deployment June 2017: - Incremental expansion of the IoT project, culminating in the citywide implementation of IoT.