Io T Ph D2020-Assignment 1

PhD Course on Smart Environments: Technologies, state of the art and research challenges

(A. A. 2019/2020)

First Assignment

In this assignment you will define an IoT service ecosystem that falls within one or more of the IoT verticals presented during the 1st lecture, see page 5 of the lecture's slides. The IoT service ecosystem must include 3 different use case scenarios, like the ecosystem "Transportation & Smart Cities" presented during the 1st lecture, see page 4 of the lecture's slides.


The first step is to define the 3 use-case scenarios that comprise your IoT service ecosystem by providing 1 storyboard for each scenario.

For example, in the ecosystem "Transportation & Smart Cities", some scenarios discussed:

  1. Sofia has an appointment downtown - she needs to find a car by using a dedicated App, or by interacting with a voice agent (e.g., Alexa), ...
  2. Sofia searchers for a parking spot, near the appointment, by using the display integrated in the car, or by interacting with a voice agent, or by using smart glasses, ...
  3. Depending on the condition of the car, an appointment with a mobile mechanic is made to change the car's oil while Sofia is in the appointment, e.g., by sending a notification to Sofia's mobile phone for confirmation.

Based on the described use-cases, provide a list of sensors that are required to implement it. For each sensor provide:

  • Property observed
  • Indicative hardware products (Link)
  • Unit of measurement
  • Resolution
  • Sampling frequency
  • Measurement Error

For example, in the ecosystem "Transportation & Smart Cities", the some scenarios discussed:

  1. Location of cars (a GPS device, units: geographic coordinate system, resolution: a few meters, ...)
  2. Mileage of car (an OBD sensor, unit: kilometers since last service, resolution: meter, ...)
  3. Parking-spot sensors (an electromagnetic sensor under the asphalt, unit: occupied/not-occupied, ...)
  4. Car Parking sensors (ultrasonic sensor, unit: meter, ...)
Bonus: Define your sensors using the Semantic Sensor Network Ontology
Bonus: Identify a dataset that is relevant to the sensor and usage scenario described in your IoT service ecosystem, e.g., from IEEE Data Port, Roma Open Data Portal, or any other Public Data set repository

Define the necessary data structure and data aggregations required to realize the 3 use case scenarios. You are free to use the tool of your choice to define the data structure, e.g., data dictionary, or a entity relationship model, etc.

If you have identified a dataset for one or more of the sensors defined, you can integrate the dataset in your data structure.

Define the data aggregation tasks that are required to realize the 3 use case scenarios defined. In case your scenarios require access to external data, also define these data.

For example, in the ecosystem "Transportation & Smart Cities", the some data aggregation tasks:

  1. Search for car within 1km from Sofia's house, order by distance.
    External data: Sofia's calendar to identify when a car will be needed.
  2. Search for not-occupied car parking spot within 1km from Sofia's appointment, order by distance.
  3. Check if car's mileage since last service is within oil specification.
    External data: Oil specification data, Car's service log.

Define a possible system architecture that can accommodate the services described. Make sure that your system architecture clearly defines where the data are stored, how data arrive to the storage service, where data processing takes place, etc.

  1. Provide a diagram of the service software components, e.g., check out the service diagram presented during the 2nd lecture, see pages 5, 6, 9, or 13 of the lecture's slides. If you wish you can use Unified Modeling Language (UML).
  2. Provide a diagram of hardware components, the network technologies used and how they are layered, e.g., check out the diagrams presented during the 2nd lecture, see pages 1, 2, 3, 13, or 14 of the lecture's slides. If you wish you can use a computer network diagram.

How To Submit

You need to create a GitHub public repository dedicated to the assignments of the course. You should use the same repository for all assignments, so make sure that your repository is properly structured. The main README.MD file should provide the following information:

  • A project title,
  • Your personal information (name, email, link to linkedin profile),
  • A short description (abstract) of your IoT service ecosystem (1 paragraph max).
  • A list of the Use-case scenarios, for each use-case scenario:
    • A name,
    • A short description (2-3 sentences),
    • A link to the storyboard image.
  • A table of the Sensors required, with all the information requested above.
  • A presentation of the data structure and data aggregation tasks, e.g., by providing the data dictionaries and diagrams.
  • A presentation of the system structure, by providing the service diagram and the device/network diagram. Make sure that each diagram is accompanied by 1 paragraph that explains the main entities of the diagram, it's structure and important details.
  • A link to a YouTube Video presentation of maximum 8-minutes with the following structure:
    • A 1-minute presentation of your idea
    • A 3-minute presentation of the 3 use-case scenarios (roughly 1 minute for each scenario)
    • A 1-minute presentation of the sensors used and related information.
    • A 1-minute presentation of the device/hardware diagram explaining the envisioned network structure, where data are stored, etc.
    • A 1-minute presentation of the software service diagram.
    • A 1-minute presentation of the data structure, where it is stored (given the above 2 diagrams), and the aggregation tasks.

The link to the github repository needs to be submitted via Google Classroom.