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280 Big Data Analytics for Connected Vehicles and Smart Cities Summary 281

dent results, the best results will always be achieved when there is a
coordination and harmony between projects and initiatives.
18. There is an emerging possibility to go beyond even the smart city to
the sentient city where sensing has been optimized and the level of
intelligence is such that appropriate strategies can always be defined
and implemented. Big data and analytics can also play a key role in
planning and operating transportation as a single system with clarity
of purpose, connectivity, adaptability, and effective status determina-
tion at any given time.
19. Be prepared to learn lessons and take advantage of practical experience
gained from other industries and from other smart city transportation
initiatives around the globe.
20. Start working on data definitions for subjective transportation terms.
Prepare the way for analytics to be applied to large-scale smart city
transportation data sets in order to identify new trends and patterns.
Also be aware of the significant differences between reporting and ana-
lytics and the need for a deep and wide data repository to get the most
from the analytics.
21. Be open to the possibility of new scientific approaches to transporta-
tion planning, traffic engineering, and work program definition.

22. Adopt a structured approach to the evolution of smart cities, taking
full account of the ability for one project to support another.
23. Develop an awareness of the new possibilities and capabilities of data
science and how these advances can be adapted to smart city transpor-
tation.
24. Begin the development of a structured cost-benefit analysis framework
for smart city transportation services, and make that the basis for a de-
tailed cost-benefit model based on detailed design of proposed imple-
mentations.

12.16 Conclusion

This book—by necessity—spans a wide area of interest. As noted previously, a
major objective of the book is to enable the building of a bridge between smart
city transportation and data science. I have had the privilege of a position at the
boundary between transportation and data science that has enabled me to ac-
cumulate insight and understanding. As expected, this experience of structuring
and documenting experiences gained has resulted in new learning and under-
standing. It is to be hoped that the book will have the same effect on its readers