IFN667: Enterprise IoT Systems - Road Emergency and Accident Management - Report Writing Assignment Help

Assignment Task:

Scenario 1: Road emergency and accident management 

The report on survivability in fatal road traffic crashes shows that the 48% of those who  died sustained non-survivable injuries. Out of the group who sustained survivable injuries,  5% were not located in time to prevent death, 12% could have survived had they been  transported more quickly to hospital and a further 32% could have survived if they had  been transported quickly to an advanced trauma centre. 

From the emergency services perspective the time between when the crash occurs and  when medical services are provided needs to be reduced. They request a solution for  emergency service providers in Australia to manage responses more effectively in order  to reduce the consequences of injury to prevent death and disability. 

The proposed design of an enterprise IoT solution can address, but not limit to, the  following requirements:  

• Send an automated message to the emergency services following a road crash  with the precise crash location. 

• Emergency call generated either manually by the vehicle occupants by pushing a  button or automatically via activation of in-vehicle sensors after a crash. 

• A set of data contains information about the incident e.g., time, location will be  sent to the operator and other stakeholders. 

Scenario 2: Bushfire management system for national parks  

Australia has suffered a devastating early bushfire season with fires across several states  burning through around 18.6 million hectares and destroyed thousands of properties with  the loss of more than 30 people and 1 billion animals. The cost of dealing with the  bushfires is expected to exceed the $4.4 billion of the 2009 Black Saturday fires and  tourism sector revenues have fallen more than $1 billion. 

The Queensland Parks and Wildlife Service management request a new IoT solution for  monitoring national parks to prevent and mitigate the bushfire risk. Monitoring the  national parks and using the collected data through sensors, not only could be used to  predict bushfire but also can help to reduce the fire damage. Factors such as climate  trends and weather patterns can contribute to the intensity of bushfire seasons. 

The proposed design of an enterprise IoT solution can address, but not limit to, the  following requirements: 

• Provide an early warning system if a fire was to unexpectantly occur. 

• If a fire begins in a remote section of the National Park, the system will notify  managers of the National Park and send a request to suitable emergency services. 

• Considering a couple of variables in data such as weather pattern, fuel moisture,  wind speed to predict the probability of fire in the area.

Scenario 3: Smart irrigation for saving natural resources 

A commercial farm would like to optimize water usage by implementing a smart irrigation  system enabled by IoT. Such a system is expected to provide the ability to detect soil  moisture and optimize water usage by only watering areas that are dry. The system  becomes even more effective when integrated with other data sources such as weather  and map data. By cross-referencing with public weather data, the system can ensure that  it does not waste water by irrigating shortly before a rainstorm. 

For example, the design of such a potential enterprise IoT solution would contain, but not  limit to, the following elements:  

• Sensors: Detect soil moisture 

• Actuators: Open and close valves within the irrigation system 

• Communication: A wireless network to facilitate data transfer between sensors,  actuators, and cloud-based software 

• Software for data processing and analytics: To receive and analyse data from  sensors and 3rd party services; to send open and close commands to actuators • Data Sources: 3rd party data services such as weather and topological maps • Software for interacting with end users: Web application with a user interface  allowing the farmer to see immediate status and historical trends 

Furthermore, the data generated by the system becomes even more valuable when  aggregated with similar data across many farms and perhaps visual crop data collected by  autonomous drones. From this collection, the relevant government body (such as the  State Department of Agriculture) is able to plan and forecast crop yields more accurately.  

Scenario 4: Asset tracking system for distribution centre optimisation 

IoT can be applied to enhancing asset tracking to optimize floor space and minimize the amount of time goods are staged for loading in large distribution centres. For example,  the design of such a potential enterprise IoT solution would contain, but not limit to, the  following elements: 

• Beacons: Low Energy Bluetooth Beacons tagged to assets 

• Sensors: Low Energy Bluetooth readers 

• Communication: A wireless network to facilitate data transfer between sensors  and cloud-based software (i.e. WiFi) 

• Service Software: Cloud-based software to receive and process location data from  sensors 

• Application Software: Web application with a user interface allowing operators to  navigate to assets 

• Integration: Integration with shipping software 

The resulting system provides the ability to map a manifest for loading a shipping  container to the warehouse location of each asset to be shipped. Further, this system  becomes more efficient when integrated with a fleet tracking system which, for example,  equips containers with GPS sensors. By cross-referencing the container arrival time with  instructions to stage assets for loading, a distribution centre can minimize the floor space  needed for staging assets by staging just-in-time. 

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