Chapter 5 discusses decision making using system modeling. The author briefly mentions an open source software tool, EMA Workbench, that can perform EMA and ESDMA modeling. Find EMA Workbench online and go to their main website (not the GitHub download site). Then do the following:

1) Under documentation, go to the Tutorials page.

2) Read through the Simple Model (in your chosen environment), and the Mexican Flu example. 

3) Decide how you could use this software to create a model to help in developing a policy for a Smart City. 

To complete this assignment, you must do the following:

A) Create a new thread. As indicated above, explain how you could use the EMA Workbench software to develop a model to help create a policy for a Smart City. Explain what policy you are trying to create (i.e. traffic light placement, surveillance camera coverage, taxi licenses issued, etc.), and what key features you would use in your model. Then, explain how EMA Workbench would help you.  

POST

Peer comment 1 Venkata Sai Charan Batchu Week 3 discussion (Decision Making Using Models)COLLAPSEBetter decision-making needs technology and strategic methods. The design and execution of a framework is essential. In IT, a framework includes the usage of models, strategies, and numerous concepts. Exploratory Modeling Analysis (EMA) workbench is one such model used widely as it is a model used in various conditions, thoughts, simulation models. The decisions made with EMA support helps in advanced planning and approaches (Kwakkel, 2017). While Mexico and the USA was fighting against the Flu, EMA was used to build frameworks to stop the spread of the disease. The model can be built in Python, Vensim, and Excel. Vensim was used as a base class to build Mexican flu. EMA is the best model to unbox the flu case. EMA was used to determine the death rate, calculate the population that is already infected with H1N1, and develop policies to reduce the spread of the disease. A smart city is said to be smarter when it has the best traffic and intelligent solutions. Light posting at positions that concur with air quality devices, cameras to monitor and manage security, traffic control, and also pedestrian safety is essential. All this information helps in better economic improvement. Planning public transportation services, improved traffic management, monitoring pedestrian activity can be enhanced by data-driven decision-making methods. Every policy implemented should be strategic and possible in terms of technology and economy. Introducing smart lights in the city will effectively reduce costs as the lights are sensitive to the movement of the vehicles. Road-surface sensors, real-time updates, and CCTV footages are smart ideas to control and manage traffic. Extreme data obtained is challenging to handle, but it can be optimized by using intelligent transportation systems (ITS) and hybrid schemes to maintain accuracy (Raiyn, 2016). The usage of solar lights is highly recommended as they save money, energy, and minimize resources. The solutions are essential to determine the traffic flow, and by using this data to clear congestion, detours can be planned to change the traffic conditions. Introducing public transport in rush hours frequently will also reduce the usage of personal vehicles, directly helping in traffic control. Passengers should be encouraged to use public transport that aids in traffic and pollution control, profit to the government, and also cost-saving and comfort to the citizens.More urban developments include improved security framework, parking facilities, and waste disposal. More charging spots for electric vehicles at shopping malls and other public areas are considered as a value-based decision. Waste management is an important area which needs improvement in every corner of the city. People should be aware of facts like reduced plastic usage and recycle management. Data should include containers used to pack various substances, their disposal methods, and patterns. By implementing strict policies in society, waste can be managed easily. Since waste disposal is directly proportional to the pollution, health, and safety of the environment, proper awareness, and strict rules need to be imposed. Other ideas for a smart city would be power-efficient lighting, clearly defined signs on the traffic areas, school zones, and pedestrian safety. EMA workbench software can be used as a success in implementing policies for the betterment of the city. It is capable of producing simpler structures using complex data, which provides positive outcomes (Joshi et al., 2016). References:Kwakkel, J. (2017). The Exploratory Modeling Workbench: An open-source toolkit for exploratory modeling, scenario discovery, and (multi-objective) robust decision making. ScienceDirect, 96, 239-250. DOI: 10.1016/j.envsoft.2017.06.054Raiyn J. (2016). Speed Adaptation in Urban road Network Management. Transport and Telecommunication, 17(2), 111-121. DOI: 10.1515/ttj-2016-0010Joshi, S. et al. (2016). Developing Smart Cities: An Integrated Framework. Procedia Computer Science, 93, 902-909. DOI: 10.1016/j.procs.2016.07.258Peer Comment 2Mounika Chowdary Polina Discussion_3COLLAPSEDeveloping a policy for a Smart CityThe EMA modeling system can be used to visualize a smart city model to understand the strategies of a smart city. Many charts and tables can be implemented to understand the mapping of a city. The budget can be drawn, and the funds can be raised beforehand to make the project run successfully.  The following steps and strategies must be made for a smart city. Smart technologies and tools must be used to make a city run on automatic techniques without much interference from human resources.Implementing smart traffic lights:The traffic lights will assist in controlling the congestion on roads. There will be no need of traffic police to stand on roads and control the traffic and that can be automatically done by the traffic lights according to the increasing and decreasing traffic. The signals must be visible to the drivers and penalization will be levied upon signal breakers. Unnecessary congestion due to vehicles can be minimized by such automatic lights (Marjuki, M. I., Yunus, S., & Ang, S. P. (2018). The drivers must be educated of the signaling of lights and one must understand the meaning of each color to drive safely on roads.Installing CCTV cameras:These cameras help in surveying the roads and penalize the drivers that break the rules. Any problems on roads can be viewed by the officers sitting in their office and the problem can be easily resolved. Any driver exceeding the speed limit can be caught by the cameras and any illegal activity can also be judged with the help of camera surveillance. The camera must be modified so that it can even work in low light and harsh weather conditions. The image quality must be high resolution. The broken bridges and bad roads that need to be repaired can be visualized by higher authority.Automatic signals on roads:These signals will raise alarm prior to a disaster so that the drivers can get alert and take the necessary precautions. Drivers driving at a higher speed limit will also be made aware of the speed breakers. The police officers will be aware of any accidents on roads and will get to know about the location of the mishap. The signals will be raised to ensure security to the drivers and passengers. Any breaking of law will be informed via these automatic signals. The automatic signals can also inform about any malfunction of the technology such as the traffic lights that require repairing.Reference:Marjuki, M. I., Yunus, S., & Ang, S. P. (2018). Minimization Of Traffic Congestions Using  Traffic Adaptive Model.Retrived from 7th Brunei International Conference on Engineering and Technology (BICET 2018).Peer Comment 3Rajendra Prasad Sabbani week 3 discussionCOLLAPSEEMA Workbench in Policy MakingEMA can be helpful when pertinent data exists that can be exploited through models building, but where this data is inadequate for determining a solitary model, i.e., a single arrangement of assumptions. Various models could be developed that would be steady with accessible data. According to Pruyt, Kwakkel & Hamarat (2013), a solitary model run drawn from a model or a lot of conceivable models is then only a computational experiment that uncovers how the framework would carry on. That is if different speculations this specific model makes about the different unresolvable vulnerabilities are right. Conducting various computational experiments makes one explore the effects of different assumptions combination. EMA helps in the decision-making process for the policymakers. MA has been used in many fields, such as energy, transport, water management, and many more. Here, we use the SD (System Dynamics) software to create models for developing policies for a smart city. SD is appropriate for the generation of plausible dynamics. They are easily manageable. EMA workbench provides support for developing models in various environments ("EMA Workbench documentation — Exploratory Modeling Workbench," 2020). Models are developed in Python. The fundamental principle is that policymakers should perform EMA on computers efficiently to create smart cities.  The utilization of such technology enables metropolitan pioneers to increase an incorporated perspective on how their urban areas' frameworks are inseparably connected. This is to maintain a strategic distance from policies that may have unintended negative impacts and to build endeavors on policies that are anticipated to have positive outcomes. The SD approach is centered on the same standards from numerous public engagement strategies. Finding a way to expand information and foresee results will help build a smart city.ReferencesEMA Workbench documentation — Exploratory Modeling Workbench. (2020). Retrieved from https://emaworkbench.readthedocs.io/en/latest/Pruyt, E., Kwakkel, J. H., & Hamarat, C. (2013). Doing more with Models: Illustration of an SD Approach. In Proceedings of the 31st International Conference of the System Dynamics Society, Cambridge, USA, 21-25 July 2013. System Dynamics Society