---
title: Internet of Things - Connected Car Use case
type: article
date: 2018-12-01
source: website
original_url: "https://navveenbalani.dev/index.php/articles/internet-of-things-connected-car-use-case/"
topics: ["iot"]
legacy_categories: ["iot"]
tags: ["iot-guide"]
summary: "This article is part of IoT Architecture Series - <https://navveenbalani.dev/index.php/articles/internet-of-things-architecture-components-and-stack-view/ Before we deep dive into connected car use case, let’s understand a vehicle in the context of IoT. A vehicle can be viewed…"
draft: false
---

This article is part of IoT Architecture Series - <https://navveenbalani.dev/index.php/articles/internet-of-things-architecture-components-and-stack-view/>

Before we deep dive into connected car use case, let’s understand a vehicle in the context of IoT. A vehicle can be viewed as a complex system comprising of various subsystems like engines, wheels, doors, brakes, etc. employing many sensors, actuators which are typically controlled by many embedded software devices called an electronic control unit (ECU). Similar to our manufacturing use cases for an elevator, the vehicle subsystems needs to be monitored and serviced through condition and predictive-based maintenance and can employ IoT to derive these insights. As the user is now directly associated with his vehicle, new insights and business models can be derived from the connected vehicle solution. We will discuss more about it in the coming sections. Let’s first start with a formal definition of a connected car. As per Wikipedia – “A connected car is a car that is equipped with Internet access, and usually also with a wireless local area network. This allows the car to share internet access with other devices both inside as well as outside the vehicle.”

From a hardware perspective, the car can
connect to the internet, through built-in telematics boxes which connect to the
Internet usually through GSM module (or
through Bluetooth or WI-FI tethering via your Smartphone if telematics box
supports its) and it’s tightly integrated with the car system. The other means
of connecting the car is to plug-in a device to the OBD (on board diagnostics)
port of the car to extract the vehicle data. The device can have an in-built GSM
module or rely on internet connection from the Smartphone through WI-FI,
Bluetooth or a USB cable.  If you search
for the term “OBD” on Amazon, you would see tons of manufacturers
providing OBD devices, which can plug into any car OBD port.

---

*Note - OBD 2 port would be generally available in all
modern cars, however you still might have exceptions, so it’s better to check
your car manual for support  (for
instance, from 1996, all cars in the US were required to be OBD II equipped,
while in India, it was mandated from mid of 2013)*

---

### IoT Strategy

Let’s talk about the connected car use
case.  With millions of cars without
pre-fitted telemetry devices, a hypothetical start-up company thought of
exploiting the area of the connected car.
The same technology from high-end cars
can be made available at a fraction of
the cost with
various value added services. The start-up company decided to target the
following use cases:

**Hardware
Devices**

- Providing OBD 2 Port device
  connector  (sourcing OBD II device and
  adding connectivity options)

**Software Services**

- Location Tracking
- Real-time performance
  monitoring of the car
- Condition based maintenance
- Predictive maintenance
- Pre-shipped performance events
  (change car oil, low tire pressure ) + location based services (nearest
  available service station)
- Creating custom alerts
  (geo-fencing, high-speed driving, weather data)
- Driver assistance
- Behavior analysis of the driver
- Recommendation based on driving
  patterns
- Speak to me (understand your
  car better)
- Connected solutions -
  Integration with home automation systems (especially for individual owners),
  after sales services, remote diagnostics, usage based Insurance, service repair
  discounts, etc.

The above use cases apply to both individuals as well as fleet management companies who could monitor cabs remotely, create alerts for driver speed, analyze driver’s behavior pattern, issue smart invoices based on maps, wait time and actual distance covered.

### Hardware Devices

Instead of manufacturing or making devices,
the start-up company partners and sources OBD 2 devices directly from
manufacturers. Using OBD 2 device, it adds the connectivity code to connect to
their cloud IoT platform and transformation code to transform OBD II port data
into a customized binary format to minimize the size of data being transferred. The device supports various
connectivity options like GSM, 4G LTE modules or relies on internet connection
from smart devices through various protocols like Bluetooth, WI-FI or a USB
connector.  The start-up company decides
to build its own customized IoT platform,
instead of using services from platform providers. We would talk about one such
open source IoT platform stack in next chapter, along with various commercial
IoT offerings.

### Software Services

The software services listed earlier are
developed and deployed as cloud services. Primarily, the OBD 2 data and GPS
location are made available continuously
to the IoT platform in a customized compressed format (think of this a zipped
JSON format).  Let’s inspect some of the
information available as part of the OBD port. The values can be retrieved by using the PIDs (Parameter Ids)
codes from OBD II port. For instance, to retrieve the vehicle speeds, the
standard PID 0D code needs to be used. Some of the informations that can be
retrieved are:

- Vehicle speed
- Engine RPM
- Diagnostic trouble codes (generic
  set of codes, but extended by car manufacture’s to add their own diagnostic code)
- Coolant temperature
- Air flow rate
- Absolute Throttle Position
- Absolute load value
- Fuel status
- Fuel pressure
- Type pressure
- Battery voltage

The above is only a minimal set of data
from the car. Your car is already equipped with hundreds of sensors and with
the car now being connected; the data
generated through the car is being utilized
for various other use cases.

Once the OBD and GSP data is available to
the IoT core platform, the platform can start consuming it. We would not go in
depth about the IoT core platform, and
more details can be found in Chapter 1 where we talked about IoT stack. To explain in simple steps, our IoT core
platform would read the continuous stream of vehicle data, uncompress the same,
persist and analyze the data, execute the required cloud services (condition
monitoring, rules, behavior analysis) and
notify the user to his mobile device.  A
mobile application or web based application is provided to the user to view the
data in real-time offered by various services. In Chapter 3, we would talk
about how to realize the connected car use case using commercial cloud IoT
offerings. Given below are the set of use cases with brief implementation
details and how the data can be visualized
in a mobile application:

**Location
Tracking:** Provides a map view and location of the
car on mobile or web application.

**Real-time
performance monitoring of the car:** Provides real-time
graphical and tabular view of the performance data of the car from OBD port

**Condition based maintenance:** We discussed this in [previous article with the manufacturing use case](/articles/internet-of-things-application-of-iot-in-manufacturing). The same approach is applicable for a vehicle, to detect utilization, detect anomaly (faults from normal deviations) and detect if maintenance is required and provide alerts.

**Predictive
maintenance:** We also discussed this earlier with
the manufacturing use case. This phase performs predictive maintenance activity
of the vehicle using the various approaches discussed earlier as part of the
manufacturing process.

**Pre-shipped
events:** Events and rules shipped as part of the
initial software and events executed till date and action taken. These are used as part of condition-based
maintenance.

**Create
custom rules and action**: Custom rules and event
created by the user or the fleet manager (managing the fleet of cars). Rules
are basically IF – THEN statements, For instance, if a teenager drives a car during a specified time interval, the
following rule can be created -

*IF vehicle speed > 80 km/h and time between 4:00 –
6:00 pm, trigger an SMS.*

*IF
GPS coordinates > geo-fencing coordinates, trigger an SMS.*

The second rule is also applicable for
fleet managers managing the fleets to track that vehicle doesn't go beyond a certain boundary or a mapped
region due to cross region license restrictions.

**Driver
assistance:** This feature provides various assistance
to the driver, like route planning which can minimize fuel consumption or advise the user not
to take the regular route due to weather conditions and suggest
alternatives.

**Driver behaviour analysis:** Classifies the driver’s ability over a period of time
based on the vehicle data (vehicle speed, RPM, throttle position, etc.),
idling, accelerometer (tracking rapid lane changes), brake pressure,
accelerator pedal position, GPS data (GPS calculated vehicle speed) and driver
past history.

The parameters can be fed into a machine
learning model which can then classify the driver as – novice, unsafe, neutral,
assertive or aggressive.

---

*Tip -
Standard OBD-II protocol doesn’t provide
parameters like brake pressure, accelerator pedal position, but it’s generally provided by car manufacturers
through custom parameter ids. The OBD hardware device should know the parameter
ids to extract the relevant value.*

---

**Recommendation
based on driving patterns:** This involves analysis of
the driver driving patterns over a period of
time and providing recommendations on how best to drive the car and
utilize the capabilities of the car. For instance, suggesting how to save fuel
based on driving patterns (driving at second gear constantly in a geared car),
less use of brakes and slowing down the accelerator instead during speed
breakers or avoiding sharp turns and yielding at specific locations (tracked
via GPS, accelerometer, and steering
angles).

**Speak
on:** This feature provides value added services
where you can speak to a car using natural language and car responds to questions
about car features or provide recommendations based on the data gathered from
above use cases.  Imagine this being a
smart SIRI system that is optimized for the connected car and understand the
context of the connected car to answer the question effectively.

**Connecting
connected solutions:** Here we will see how data from the connected car can be used by other
connected systems. We list some of the use cases below -

- After Sales services – This use
  case involves how after sales services and maintenance activity would change
  for providing better service maintenance and monitoring based on actual usage
  and identify car break down before and suggest corrective action. We went
  through the set of elevator manufacturing use cases earlier, and the same is applicable for maintenance activity for a
  connected car.
- Usage-based insurance – This
  use case involves how Insurance companies can utilize the data from a connected
  car like actual utilization and driver behavior
  analysis for creating personalized car insurance quotes.

Integration
with connected systems – This use case
provides rules and connectivity via exposed APIs in a secure way to connect
with other connected systems – like home automation. For instance, starting
your coffee machine as soon as your car reaches x distance from your home or
reserving a parking lot before your car reaches the shopping mall. The other
use cases are using the connected car data for autonomous driving, smarter
cities (traffic management), etc.