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smartROAD Evaluation

Final Report

Hamburg, October 31, 2016

Evaluation – The Final Report smartROAD Project Page I

Disclaimer This document is intended for the internal use of recipients only and may not be distributed externally or reproduced for external distribution in any form without express permission of the Hamburg Port Authority AöR.

Main Author: Dr. Phanthian Zuesongdham Jan Krause

Evaluation – The Final Report smartROAD Project Page II

Document History Version Date Author Remarks 0.1 September 12, 2016 Dr. Phanthian Zuesongdham

Jan Krause First Draft

0.2 September 15, 2016 Dr. Phanthian Zuesongdham Jan Krause

Incorporated comments from partners.

0.3 October 17, 2016 Dr. Phanthian Zuesongdham Jan Krause

Incorporated comments and new inputs from partners.

0.4 October 25, 2016 Dr. Phanthian Zuesongdham In corporated final comments from all partners

1.0 Oktober 31, 2016 Dr. Phanthian Zuesongdham Jan Krause

Internal QA

Evaluation – The Final Report smartROAD Project Page III

Table of Content 1. Preamble 1

2. Executive Summary 2

3. From Idea Creation to Business Case 3

3.1 Idea Creation and Scoping 3

3.2 Planning and Implementation 5

3.3 Business Case – Cost Indicator 8

4. Evaluation Methodology 9

5. Summary of Basis Input for smartROAD Evaluation Report 11

6. Evaluation Results 20

6.1 Horizontal Topic: Network Communication and Data Centre 20

6.2 Horizontal Topic: Integrated Information Platform 22

6.3 Use Case: Smart Traffic 23

6.4 Use Case: Smart Lighting 26

6.5 Use Case: Smart Structural Sensing 28

6.6 Use Case: Smart Environment 30

7. Future Potentials and Recommendation 32

8. Conclusion 34

Annex 1 – Summary of the result of the data validation according to the basis requirements in the evaluation 35

Table of Figures Figure 1: Architecture Overview smartROAD 5

Figure 2: Test Segments in smartROAD 6

Figure 3: Overview of the Implementation Map 7

Figure 4: The sensors’ locations of the test segment A-B Kattwykbridge 7

Figure 5: Horizontal topics and use cases included in the evaluation 10

Evaluation – The Final Report smartROAD Project Page 1

1. Preamble The Smart Road project aimed at demonstrating intelligent road application cases on selected road sections in the Port of Hamburg. Apart from traffic and incident detection and traffic management options as well as adjustable pedestrian and cyclist lighting, the project showed how modern sensor technology collects and depicts impacts and effects by traffic on infrastructure construction and environmental data. Under the framework of the Memorandum of Understanding (henceforth: MoU) between the Free Hanseatic City of Hamburg (henceforth: the FHH) and Cisco, signed on April 30, 2014, smartROAD was one of the projects fulfilling the ambition and strategy of FHH on Digital City as well as the ones of the Hamburg Port Authority (henceforth: the HPA) on smartPORT Hamburg. In co-operation with partner companies all the relevant Information Communication Technology (henceforth: ICT) systems, sensors, video cameras and network communication components were installed along the selected road sections in the Port of Hamburg to advance the idea of a smartPORT. On the selected roads in the Port of Hamburg the Smart Road project demonstrated what an intelligent road can offer. The roads chosen were Hohe Schaar Street and Kattwykdamm, including the Kattwykbridge. These are the one of the Hamburg Port’s main routes. Four application cases were tested here:

• Smart Traffic was to determine and depicted the current traffic situation. Data on traffic flows, vehicle categories and traffic volumes were collected. Traffic incident could also be detected. Privacy of individuals was protected using dedicated software.

• Smart Lighting introduced an adjustable lighting control system. If pedestrians or cyclists were on the pavement of Hohe Schaar Street, the luminaires would adjust the light level. Sensors detected person’s movement and the street light above as well as the next five lights would shine brighter. Afterwards, the lights would dim down again. Moreover, the use case included the exchanges of the conventional luminaires into LED-luminaires which reduced the energy consumption in the test area and could be centrally controlled by the cloud-based control system.

• Environmental data were collected under the Smart Environment use case. Various sensors measuring parameter like wind speed and direction, precipitation, air temperature, pressure, and humidity. Furthermore, they collected data on fine particulate matter (or PM10), carbon monoxide, sulphur dioxide and nitrogen oxides.

• Smart Structural Sensing monitored the condition of the infrastructure. Under the project this was demonstrated using structural sensing at Kattwykbridge. For the Kattwykbridge data has been collected on the strain and tilt in the structure of the bridge and in particular the pylons as well as vibrations caused in particular by trains and trucks.

All data obtained were merged in a central application. This application offered functionalities to evaluate the data and to visualise them. Various departments of the HPA tested it as an integrated information and management tool (Smart Analytics), for example facility or traffic managers as well as the environmental department. The implementation of the use cases with the Internet of Thing (henceforth: IoT) technologies in smartPORT was perceived as the IoT project of the first kind integrating the network communication, sensors, video camera in a holistic approach on a real physical infrastructure in the port. It was finished to the opening of the IAPH World Port Conference 2015 in Hamburg where the HPA was honoured to be the host of this renowned event in the seaport industry. The test area of smartROAD were conducted from June 2015 – October 2016.


2. Executive Summary In the project smartROAD, numbers of use cases in the context of IoT were implemented with all the combination for the first time of the project of this kind. The project was divided into three phases: Plan – Build – Run.

• In the “Plan”-phase, the project team engaged with the conceptual work on use cases, business cases, scoping, solution architecture and the planning of the implementation.

• In the “Build”-phase, all the installation and integration works were conducted to have the use cases ready for the evaluation phase. This also included the preparation of the support contract of the use cases in the test period.

• In the “Run”-phase or evaluation phase, the user groups of the HPA investigated and assessed the use cases. The experiences and findings gained from the project were discussed and shared among the project partners.

This report is one of the deliverables in the “Run”-phase. It is based on the interim report released in October 2015. It describes shortly the use cases, the business cases of the project and the evaluation results from the experiences and findings of the first evaluation phase covered the period of June 2015 – October 2016. Four aspects to the evaluation were made in this project: 1) Business Case, 2) Quality, 3) Transferability and 4) Project Lessons-Learned. The findings and experiences described in this report showed numbers of the successes, challenges, stepping stones and opportunities for improvement to the solution in the project. These are valuable for the further developments in the following projects to come in the context of smartPORT Hamburg and Digital City of the FHH. Therefore, at the end of this report, some potentials for the future and recommendations are summarised by the project team.


3. From Idea Creation to Business Case This chapter describes the initial idea creation of the project and the findings of the project with proof-of-concept character used for the business case definition. 3.1 Idea Creation and Scoping At the beginning, four aspects of the smartROAD idea were created according to the NABC-Method of Stanford Research Institute. Needs: To fulfil the strategy of the HPA’s smartPORT Hamburg, the intelligent infrastructure is a pre-requisite to run an efficient traffic management with in the port.

1. Road traffic has always been a challenge of the port of Hamburg to manage according to their free access for all kind of vehicles. Traffic volume in the port is increasing every year, a precise and reliable detection of road traffic with more information like vehicle classification, speed, traffic volume, etc. are the critical parameters for the prognosis capability.

2. Furthermore, maintenances can mostly be done when the relevant road sections or bridges are closed. The real-time information on the bridge health condition could help the engineer and technicians judge in the planning of maintenance work.

3. On a road with high traffic volume with mixed structure of the road users like port, safety is one of the main Topic to be improved. Any accidents could trigger a huge traffic congestion, personal and property damages.

4. Hamburg has a big challenge of being port and city at the same time because of the physical area which is interlocked in the heart of the city. Environmental Topics are therefore a main concern for the residents living in the port area. All activities of the port stakeholders can have influences to the air quality including the traffic volume caused by them.

5. Increasing traffic volume by all modes of transport can only be managed by more efficient and intelligent use of the infrastructure beside maintenance measurements of the physical condition of these infrastructural objects and surfaces.

Approach: According to the needs mentioned above, the big picture use cases were developed to be the proof of concept for these challenges as described below:

1. Use Case: Smart Traffic A precise detection of the road traffic with modern technology like video camera and analytic software could enhance the traffic management systems which are implemented in Hamburg Port.

2. Use Case: Smart Structural Sensing The health condition of the critical infrastructure like Kattwykbridge can be monitored by mean of different specific sensors to deliver the exact parameters which are needed for the predictive maintenance of the bridge. Also by a detection of a specific change in the measured values, a damage can be notified at an early stage.

3. Use Case: Smart Lighting To increase safety on the road, the adaptive lighting concept so-called “Follow-me-Lighting” could be implemented. The pedestrian and/or cyclist are detected by sensor as they are approaching to the test area, the street light will be dimmed up to provide more visibility on the street. At the same time, they will be better recognised by other bigger vehicles on the road such as truck or personal cars. The light follows the pedestrian or cyclist in the direction they are moving. The luminaire behind them will be dimmed up as they are gone.


4. Use Case: Smart Environment Environmental parameters can be measured by air quality (CO, SO2, NO2, NO, PM10) and weather transmission (pressure, wind speed, precipitation, humidity, temperature). The sensors should be placed in a location where a congestion of traffic would be most probable like the waiting line before a bridge or a road intersection.

5. Use Case: Smart Analytics All data collected in each use case can deliver a pattern which can be used for further analysis. For example, the correlation of the traffic volume with the vehicle classification and the bridge health condition or air quality parameters could be used as hints or driver to the definition of necessary measurements.

Benefits: The finding and experiences of the project should help the HPA in the further development and deployment of new technologies in the area of Internet of Things (henceforth: IoT) and Big Data. These enable the opportunities to find out future business benefits i.e. creating new business models, not only for the port but also for the city. Competition: The digitalisation with IoT and big data is the megatrend of this decade. The HPA is until now perceived as the innovator in this field in the port industry. However, each port in this world is working also towards these trends. With the continuous development and being the trend-setter, the HPA can create image of the Port of Hamburg as the advanced technological hub and the quality port fulfilling the strategic goal on smartPORT Hamburg.


3.2 Planning and Implementation After the definition of scope and use cases to be implemented in the project, the planning phase covered the architecture, detailed specification, procurement plan and installation plan. First of all, the network and application architecture (see figure 1) was defined to be a blueprint and a common understanding among the partners for the planning and implementation.

Figure 1: Architecture Overview smartROAD The detailed explanation of the architecture is described in the document “HPA smartROAD Architecture Specification v.4” approved in September 2014. From this point, a detailed specification was created for each use case:

1. Smart Traffic 2. Smart Lighting 3. Smart Structural Sensing 4. Smart Environment

Within these documents following main Topics were described: 1. Detailed use case description 2. Scenario description 3. Technical components to be deployed 4. Installation guide and technical specification of each component

Based on the above-mentioned details, the procurement and installation plan were created in consideration to relevant factors like lead time, interdependencies with other construction projects of the HPA implemented in the same area, etc. The installation period was from February – May 2015.


The below matrix shows the implementation area with the use cases (UC):

Segment UC: Smart Traffic

UC: Smart Lighting

UC: Smart Structural Sensing

UC: Smart Environment

A-B: Kattwykbridge X X X B-C: Kattwykdamm X1 C-D: Hohe- Schaar North

X X

C-E: Hohe-Schaar South

X2 X

The figure 2, 3 and 4 illustrate the test segments, the sensor location as well the network area implemented as the pilot in this project.

Figure 2: Test Segments in smartROAD

1 In this section, only the luminaires were replaced without the implementation of the “Follow-Me-Light” concept. 2 The Smart Traffic use case at this section was implemented during October 2015 – October 2016 as an additional segment for the evaluation.


Figure 3: Overview of the Implementation Map

Figure 4: The sensors’ locations of the test segment A-B Kattwykbridge In total, following components were implemented for the test case in this project:

• 40 Access Points including Server Components for Network Communication Infrastructure Setup

• 21 Video Cameras • 102 Luminaires • 60 Thermal / Movement Sensors • 12 VW Strain Gauges • 10 Tiltmeters • 1 Air Quality Sensor • 1 Weather Transmitter • 1 Accelerometer


4. Evaluation Methodology In the evaluation phase of the project smartROAD, following steps were conducted to achieve the expected evaluation results: Step 1: Defining the quality indicators by all stakeholders in the project. These indicators included

- Solution Performance: How stable and reliable does the whole solution to the use cases performs?

- Technology Fit: To what extent do the implemented technologies fit to the defined use cases?

- Data Quality: Comparing to the experiences of the experts, do the data collected by the technologies implemented deliver the quality as expected? Can the expert groups use the data for their other analysis purposes?

- Energy Efficiency: Comparing to the use case baseline, if any, how does energy consumption change after the implementation of the new technology?

- Total Cost of Ownership: According to the resources dedicated to the realisation of these use cases, what are the cost indicators for the whole project?

- Safety Benefit: To what extent could the implemented technologies increase the safety level in the test area?

- Future Potentials: What are the potentials to replicate or to adapt these use cases into other areas such as other port areas or the city?

- Recommendations: What are the recommendations by experiences from the project for other implementation projects of the same kind?

- Project Lessons-Learned: What are the lessons learned which all project stakeholders gained in the project and which could be shared and used to improve the quality of projects of the same kind or in general?

Step 2: Classifying these indicators into following evaluation clusters: Business Cases, Quality, Transferability and Project Lessons-Learned

- “Business Cases” covers the indicators: Total Cost of Ownership3, Safety Benefit, Energy Efficiency

- “Quality” covers the indicators: Technology Fit, Solution Performance, Data Quality - “Transferability” covers the indicators: Future Potentials, Recommendations - “Project Lessons-Learned” covers the indicator: Project Lessons-Learned

Step 3: Conducting workshop-series for collecting experiences and finding by the project stakeholders for each use case and horizontal Topics (see figure 5). At the same time, the monitoring and statistical values which were already available in the evaluation period as well as further information needed were considered for the discussion and analysis.

3 See chapter 3.3 for the details.


Figure 5: Horizontal topics and use cases included in the evaluation Step 4: Consolidating the experiences and finding in the Interim Evaluation Report for the period of June – October 2015 Step 5: Reviewing and complementing the additional experiences and finding to consolidate in the Final Evaluation Report to be launched by October 31, 2016.


5. Summary of Basis Input for smartROAD Evaluation Report This chapter summarises the information of all implemented sensor types as well as their purposes, the expected values as requirement profiles for the use groups of the HPA. The information were used also as a basis of the evaluation results of the use cases described in the chapter 6.

Sensor type What does the sensor type measure?

Why do we need this data?

Remarks

Strain Gauge Tension or stress of the metal structure (in µƐ4)

For monitoring and control strain and stress value of the bridge

Deployed sensor:

Sensor Name VWS-2025

Resolution 0.4 µƐ

Strain Range 3000 µƐ

Accuracy +/- 0.1% to +/- 0.5% FS

Non-Linearity < 0.5% FS

Data measuring interval: every 5 Minutes

Tilt Meter Inclination Output (V/°)

For monitoring possible differential settlements and vertical lift effects on the bridge, it is proposed the installation of tiltmeters in piers, abutments and pylons.

It will be possible to correlate this data to the temperature, wind, traffic volume, and the sediments of all measured parameters Data measuring interval: every 5 Minutes

Accelerometer / Seismic Sensor

Balance vibration level For monitoring accelerations and dynamic displacements. Multiple parameters can be

The deployed sensor is a three-axis-seismic sensor with following specification:

4 Micro-Epsilon




Remarks

obtained to assess the structural integrity of the bridge. For example: Determination of natural frequencies and mode shapes.

Air Quality Sensor

NOx as NO and NO2 (µg/m³) SOx (µg/m³) CO (mg/ m³) PM10 (µg/m³)

In order to protect human health and environment, the EU drew up DIRECTIVE 2008/50/EC on Ambient Air Quality. With the Ordinance on Air Quality Standards and Emission Ceilings (39. BImSchV) the German Government transposed the EU directive into national legislation. (39. Verordnung zur Durchführung des Bundes-Immissionsschutzgesetzes Verordnung über

Limits:

Pollutant Limit value

Time reference

No. of allowed exceedings /

year µg/m³

or *mg/ m³

SO2 350 1 h 24

125 24 h 3

NO2 200 1 h 18

40 year -

PM10 50 24 h 35

40 year -

CO 10* 8 h -




Remarks

Luftqualitätsstandards und Emissionshöchstmengen) All cities in Europe use these parameters to evaluate the air emission level.

Weather Station

Barometric pressure (in ppm) Temperature (°C / °F) Humidity (%) Wind speed (kph / mph) Wind Direction (N/E/S/W/NE/NW/SE/SW) Rain (mm)

To obtain the basic weather information for further uses, for example, to interpret the air quality data in the context of the respective weather condition

Barometric Pressure:




Remarks

Air Temperature:

Humidity:




Remarks

Wind Speed and Direction:




Remarks

Precipitation (Rain):




Remarks

Video (incl. Analytics)

Periodic measurements of traffic volume, speed and lane occupancy (Level of Service of the street or LoS) per traffic segment Traffic volume in number of vehicles Speed (km/h) LoS (Scale 0 – 1)

Traffic volume: The usage level per traffic segment as well the number of the vehicle per vehicle class (the more number of the trucks, the higher the pressure of the street surface (normally 10 times higher – according to the traffic study) Speed: how fast are the vehicle on the traffic segment? The faster the speed of the truck, the reaction time and the forces of the acceleration process will have much impact to the street surface. Level of Service (LoS): The quality level of traffic based on performance of speed, traffic volume and time period.

LoS according to German HBS is defined as follows:

For the visualisation purpose in the CityMind, a setting value derived from the Highway Capacity Manual (HCM) which is equal to German HBS as shown in the graphic below is used:




Remarks


Correlation Requirement

Required by which user group?

Which findings are expected by the user groups?

Remarks

Traffic volume / Air Quality

L22 and S23 If the traffic volume has a significant impact to the air quality in the measured area

Air Quality / weather condition

S23 If the weather situation has a significant impact to the air quality in the measured area

Traffic volume / Speed per classification of the vehicle / Bridge Structure

L22 and L23 If traffic volume and the speed of each vehicle class have a significant impact to the bridge structure (strain, inclination, vibration)

Weather / Bridge Structure (Inclination)

L23 If the weather (especially wind) has a significant impact to the bridge inclination and when (i.e. while lifting / opening process)

Wind / Air Quality /Traffic Volume

L22 and S23 If the wind direction and the wind speed have a signification impact to the air quality measured in the defined area, when the traffic volume is high.


could be processed by other applications for analytics, view or storage. There was a limitation despite the implementation of the data privacy protection application in regard to the personal data. This was the anonymizing of truck inscription (company label, advertising inscription), which was classified by the Hamburg Data Privacy Officer as personal data. As a result of an intensive investigation, the higher level of pixilation would impact very strongly the image quality, such that the analytic of those video streams did not work properly and could not deliver the results as expected in the use case Smart Traffic.

Transferability This kind of the network communication can be transferred to other areas. However, it should be investigated before what kind of use cases will be implemented to the network area as well as the premise on the physical infrastructure in order to define the right solutions. Otherwise, the cost of this kind of the network could be too high for some areas. In regards to the data privacy protection, the concept of the anonymizing video stream for the analytics purpose could be reused in the other projects of the same kind. However, it has to be checked if any adjustment has to be done.

Project-Lessons-Learned Data privacy protection aspects including legal authorisation should be considered in the preparation and conceptual phase as early as possible in the project to identify the risks and interdependencies with other activities within the project. The setting of the network communication in this project was made for a very short term. For a productive operation the setting requires integration of all network components into an existing network operation management as well as solid risk mitigation measures especially for the issues on stability and security in the support concept. Some of such components were already implemented in the evaluation phase e.g. to achieve a better monitoring of the system stability. Especially in the run phase, clear responsibilities for each technology must be defined. This could affect the deployment, operating and service of the whole system. The definition of business-impacts, KPI’s and measurements as well as project-budget must be conducted together with the key-stakeholders (e.g. end-users) including start- and end-date in a written form as a requirement concept and agreement. If the project of this kind would run as a pilot project again, the next steps after the pilot according to the results (as a function of the success related to the KPI’s, e.g. how to handle pilot-equipment, how to rollout if all KPI’s met etc.) are to be defined. The up-to-date documentation is a key success of the incident and problem management of the run system: focusing on value-at-stake (including documentation), technical planning and documentation (including e.g. passwords, network-plan, responsibilities, process of actualizing of the documentation, operating).


the expected quality of the information required, for instance, less precision on detection of the classification of vehicles or the number of vehicles when many vehicles were queued up closely to each other, missing traffic detection zone of the test area, North of Hohe-Schaar-Street, ability to detect motorcyclist, etc. This was caused by the suboptimal placement of some cameras. In the project, one of the key conditions in the project was not to conduct any adjustment in the physical infrastructure. Therefore, the camera placement could not be done optimally. During the re-negotiation of the service contract to the pilot installation, the system was not fully serviced resulted in the several outage periods and therefore lacking the data in these periods. As there was no guaranteed service level in this pilot installation, if any incident occurred, no data would be collected during the recovering time of the system. Therefore, there were some intervals that no data was reported. The anonymization of the video camera information was in accordance to the requirements of the HPA data privacy protection officer. Persons in the video were pixelated automatically. In total video camera is another comprehensive means for the traffic detection. In the case of smartROAD, the video streams in combination with the analytics software could deliver mostly the data in the expected range of value for traffic in terms of speed, volume and Level of Services. However, there were some discrepancies in term of the speed of vehicles. Sometimes the values were very high and not reasonable i.e. 500 km/h. The reason was lying at the angle of the camera as well as the sunlight position which could influence the accuracy and the performance of the analytics capability when detecting speed.

Transferability In principle, the idea on more precise detection of the traffic situation via video camera is the state of the art, and can be transferred to the road with high traffic. The crucial factors for this use case are the selection of: 1. the camera type, to fulfil the requirements of data privacy

protection, the most appropriate choice would be thermal camera, and

2. the analytics software of which functionalities are corresponding to the needs of the use case.

3. the placement of the camera which is critical to quality to the detection results.

At the time of the project finalisation, there is already different HD or 4K video camera products which already have analytics software as well as the anonymizing features as embedded technologies. This type of the camera should be considered for the use case Smart Traffic or alike to avoid the issues on Data Privacy Protection in the implementation.

Project-Lessons-Learned An early adjustment with the existing systems for traffic control is necessary.


The placement of cameras was not optimal at Hohe Schaar Street. In the future project of this kind, the camera placement concept has to be carefully and properly defined such as the location, angle, height, etc. in order that the use case has the optimal input to deliver the expected results from the analytics application. Furthermore, central video processing requires a “classic” network infrastructure with an adequate bandwidth to guarantee the continuity of the services.


reporting time. In the operational point of view, when a luminaire alerts as defect or failure, this has to be investigated and treated immediately which causes more operational resources for maintenance and repair work. Moreover, within this test period, more than 24.000 incidents were detected by the control and monitoring system CityTouch reported to the operators. Most of them were not real incidents. In other case, as a luminaire was defect, the system kept repeating the report of the incident. Therefore, the number of the incident went so high. As a result, the control logic, incident and event management of CityTouch, has to be improved. CityTouch was still a new application of Philips. With this project, Philips could gain the experience to further develop its system. The new LED-luminaire type, Urban Sky, installed on the Kattwykbridge is well accepted by the bridge control officer because of the light quality and the good visibility in the foggy situation which is a very important aspect of bridge and vessel traffic safety.

Transferability Both aspects of this use case, follow-me-light concept and LED-luminaire replacement, is transferable to a few areas of port and the city with special requirements. However, the dedicated area has to be fit to this use case. Not all streets will require follow-me-light.

Project-Lessons-Learned Installation sites for the follow me light concept have to be selected carefully to achieve an effective result. When working on the Smart Lighting concept, the architecture of the street like distances between the light poles is critical to the desired light level of the use case. The installation of IoT technology with the chosen communication architecture for the other smartROAD use cases beside smart lighting (WLAN Mesh Network; supply of WiFi access points through power supply of the light poles) leads to more energy consumption. Therefore, a definition of the Key Performance Indicator should be carefully selected i.e. KPI on energy saving might not be able to be achieved.


risks which could occur during the installation periods causing the possible delay. Prior to the decision on procurement and installation of the complete set of sensors in the planned use case, a proof of the sensor quality should be done with few numbers per sensor type. After the quality of the data delivered by the sensors is verified, the complete set of sensors can be rolled out. In many cases it is sufficient to have just a trend for the measured values. So that we can react if a value approaches a threshold value. Exact values are often not necessary


project. Specify the needed data requirements to answer your questions. Chose a sensor with a performance (i.e. limit of detection, accuracy, range levels) that meets your data requirements and document it. It is crucial to understand and to control the sensor settings as well as to be able to do a troubleshooting at different levels. It is necessary to have a valid sensor documentation (technical spread sheets, user manual, calibration protocols, etc.). It is important to have a technical support service that knows the measurement techniques of the specific sensors and not only for IT components. The data recordings need to be checked straight after installation of the sensors in the field. A Calibration of the sensors has to be done on site in in the working environment of the sensor and has to be checked in interval. Regarding all the topics above, the project was a very good possibility to get a lot of experiences about sensors and their handlings.


• Especially the analytic of the structural, traffic and weather data can potentially identify events or problems and may create new and important insights in real time.

UC: Smart Traffic • The selection of the analytics software to detect the incidents and the events is the key success factor of this use case. The investigation of its functionalities and the capabilities has to be conducted carefully in the implementation project. Moreover, the integration of the interfaces into this software and the visualisation of the information platform has to be proved.

• The future potentials of using camera which is detecting the traffic are to add further use cases into the same cameras such as for surveillance purpose of locks and bridges, ship traffic monitoring, vehicle classification, etc.

• As the price of the thermal camera has been decreasing overtime, its deployment should be considered in such a use case in order to fulfil the compliance concerning data privacy protection.

• Travel Time Measurement is an important feature for Smart Traffic. This should be considered in a next project.

UC: Smart Lighting • The selection of the sensor technology for the implementation of the follow-me-lighting concept is the critical success factor of the use case. In this project, the thermal sensor is not the optimal solution, as so the camera due to operational constrains in the invisible weather condition like fog or haze.

• Another use case which could be derived from Smart Lighting is to influence the traffic by using light channel.

• The coverage area of the LED-Luminaire has to be modelled and simulated for the implementation area with two critical factors: 1) the distance between the poles; 2) the height of the light spot.

• As various sensor technologies consume different amount of electricity, the consideration on what sensor to be implemented in which area for which use case shall be done carefully.”

UC: Smart Structural Sensing

• With the new findings on the usage of the measured values from the sensors on the bridges for the inspection purpose without blocking the traffic, it opens the new opportunity to implement this use case to further objects in the port and in the city area without further complication and huge adjustment. The exchange with LSBG, Hamburg should be taken place.

• Strain gauges will be tested on bridge over the flood barrier Sperrwerk Billwerder Bucht. The bridge is over 50jears old and cause of construction as a small box girder not possible to inspect manual. Therefore it is in 2016/17 planned to install strain gauges in locations where damages are suspected.

• However, the planning of how the installation of the necessary sensors, their positions and the connection to the network communication has to be done carefully. The installation work on different surfaces should be tested before in order to define the right required materials and equipment.

UC: Smart Environment

The selection of the respective sensor technology, its recording reliability and its troubleshooting possibilities are the critical success factors of this use case.


General recommendation about sensor location

• Distance of different sensors, which should be correlated directly (e.g. traffic-measurement, environment, infrastructure-sensing), has to be defined as a close and respective area.

8. Conclusion The use cases of the project smartROAD were implemented and evaluated. Numbers of new findings, challenges and obstacles have arisen in the project. The project team learned to cope with new situation together to make the solution work. Even though, the implementation of such a project like smartROAD is still at the beginning. The future potentials and recommendations are numerous as summarized in the chapter 7 and depict further possibilities how these could develop and enhance working and living quality in the next decades. As the megatrend on the Internet of Things, Big Data, Learning Machines, etc will go on, the more experiences and knowledges in the project can be used and transferred in the future projects and plans, the more Return-On-Investment (ROI) can be expected from these new technologies to enhance the digital business transformation of the HPA and the Free Hanseatic City of Hamburg.


Annex 1 – Summary of the result of the data validation according to the basis requirements in the evaluation Please note that the information in the table is also reflected in the chapter 6 in the description of the evaluation result.



Validation Result

Strain Gauge Tension or stress of the metal structure (in µƐ5)

For monitoring and control strain and stress value of the bridge

The sensors delivered the data in the expected value unit. However, for monitoring and control purpose the pilot period was too short.

Tilt Meter Inclination Output (V/°)

For monitoring possible differential settlements and vertical lift effects on the bridge, it is proposed the installation of tiltmeters in piers, abutments and pylons.


Accelerometer / Seismic Sensor

Balance vibration level

For monitoring accelerations and dynamic displacements. Multiple parameters can be obtained to assess the structural integrity of the bridge. For example: Determination of natural frequencies and mode shapes.


Air Quality Sensor

NOx (as NO & NO2) (µg/m³) SO2 (µg/m³) CO (mg/ m³) PM10 (µg/m³)

In order to protect human health and environment, the EU drew up DIRECTIVE 2008/50/EC on Ambient Air Quality. With the Ordinance on Air Quality Standards and Emission Ceilings (39. BImSchV) the German Government transposed the

The sensor could not deliver the expected range of value as it was not refined enough according to the standard requirement. The sensor itself was not appropriate for the purpose of the use case.

5 Micro-Epsilon




Validation Result

EU directive into national legislation. (39. Verordnung zur Durchführung des Bundes-Immissionsschutzgesetzes Verordnung über Luftqualitätsstandards und Emissionshöchstmengen) All cities in Europe use these parameters to monitor the air emission level.

Weather Station

Barometric pressure (in ppm) Temperature (°C / °F) Humidity (%) Wind speed (kph / mph) Wind Direction (N/E/S/W/NE/NW/SE/SW) Rain (mm)

To obtain the basic weather information for further uses, for example, to interpret the air quality data in the context of the respective weather situation

The sensor delivered the data in the expected value unit.

Video (incl. Analytics)

Periodic measurements of traffic volume, speed and lane occupancy (Level of Service of the street or LoS) per traffic segment Traffic volume in number of vehicles Speed (km/h) LoS

Traffic volume: The usage level per traffic segment as well the number of the vehicle per vehicle class (the more number of the trucks, the higher the pressure of the street surface (normally 10 times higher – according to the traffic study) Speed: how fast are the vehicle on the traffic segment? The faster the speed of the truck, the reaction time and the forces of the acceleration process will have much impact to the street surface. Level of Service (LoS): The quality level of traffic based on performance of

The video streams in combination with the analytics software could deliver mostly the data in the expected range of value for traffic in terms of speed, volume and Level of Services. However, there are some discrepancies in term of the speed of vehicles. Sometimes the values were very high and not reasonable i.e. 500 km/h. The reason was lying at the angle of the camera as well as the sunlight position which could influence the accuracy and the performance of the




Validation Result

speed, traffic volume and time period.

analytics capability when detecting speed.

The below table show the correlation defined to investigate in this use case and the validation result.

Correlation Requirement

Required by which user group?

Which findings are expected by the user groups?

Validation Result

Traffic volume / Air Quality

L22 and S23 If traffic volume has a significant impact to the air quality in the measure area

Since the air quality sensor did not work, this correlation cannot be validated.

Air Quality / Weather

S23 If the weather situation has a significant impact to the air quality in the measured area


Traffic volume / Speed per classification of the vehicle / Bridge Structure

L22 and L23 If traffic volume and the speed of each vehicle class have a significant impact to the bridge structure (strain, inclination, vibration)

As the observation period in the project for the bridge structure was too short, no direct correlation between the mentioned parameter could be confirmed and could not be elaborated about their relation accurately.

Weather / Bridge Structure (Inclination)

L23 If the weather (especially wind) has a significant impact to the bridge inclination and when (i.e. while lifting / opening process)

As the observation period in the project for the bridge structure was too short, no direct correlation between the mentioned parameter could be confirmed and could not be elaborated about their relation accurately.

Wind / Air Quality / Traffic Volume

L22 and S23 If the wind direction and the wind speed have a signification impact to the air quality measured in the defined area, when the traffic volume is high.


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