By Sanchit Mittal, Co-founder and CTO, VOGO
Two-wheelers have always been the lifeline of the Indian Mobility ecosystem. The majority of the workforce in the country runs & relies on two-wheelers for decades.
The recent shift from owning a scooter towards sharing it on a need-to-use basis has been adopted & appreciated by most users. This adoption was supported & accelerated mainly by the cutting-edge technology brought by private companies recently. It has vastly improved the process of booking a rental scooter, unlocking it, riding, and returning the vehicle safely. All these phases are powdered by intelligent Data Science algorithms (AI/ML) and Internet of Things (IoT) at its core.
This technology innovation has led the consumer use-cases to increase from just daily-work-commute to food delivery, leisure activities, small-time chores & needs. Also, the fact that a large user-base is already well versed with riding scooters have contributed to this early adoption.
Impact of AI/ML/IoT on the commuter’s experience:
Step 1: Booking a scooter
In the past:
The booking process used to be reasonably old-school. A fleet manager would manually assign a scooter to a consumer by writing the commuter’s name and driving licence number on a notebook or on a spreadsheet.
In the present:
In some select cities, a technologically better & more scalable process has been tried out by many private companies. Whether commuters are at their home or Malls, or a Metro station or their friend’s place, they can locate nearby available scooters on their Mobile app. In the app, they can also view basic vitals – such as fuel level, presence of helmet, sanitization status to choose a better-suited scooter for their needs.
IoT smartness inside each scooter powers this whole experience. The GPS device, the retrofitted sensors, and the sim card in each scooter send the data about its vitals to servers, potentially every couple of seconds.
In the future:
1. This new app-based booking experience will wild-spread throughout India.
2. Choosing a particular scooter will be assisted by the scooter vitals based predicting algorithms behind the scenes.
3. AI/ML will alert a user based on current location if there is any available scooter nearby and choose a perfect scooter for his/her needs. This move will be assisted by private and public tie-ups as more scooter-sharing gets integrated into the mobility ecosystem.
Step 2: Unlocking of the booked scooter
In the past:
On booking, Consumers were given the scooter key to carry with them. There were numerous challenges in scaling safe management of this. Also, key duplicates were being made. And many consumers would misplace or lose the keys before their return time.
In the present:
Once they locate their preferred scooter, they can start the ride within 10 seconds by scanning a QR code, limiting physical touchpoints in the overall commute. No wait times, no one to interact or negotiate with. This unlocking part is powered by IoT and many checks & suggestions by smart ML algorithms continuously running on the servers.
In the future:
1. Scooters will soon be unlocked without the commuter having to take out his phone or when cellular network is not strong. Automotive-grade biometric face scans and fingerprint sensors will be installed on scooters, ensuring a smooth customer experience.
2. Various private or public ID cards like Metro cards will be integrated and also act as a payment solution. Making the first step of booking practically not required. Subsequent rides will be as seamless as just tapping an ID Card to the scooter dashboard, and user-authentication & payment will happen instantly.
Step 3: Riding towards the destination
In the past:
Commuters had to call the customer support for any issue or to extend the duration of their booking.
In the present:
The ride experience is optimized by real-time fuel status alerts, geo-fencing alerts, and over-speeding alerts in the mobile app. Plus, many support options like extending ride duration are available as one-click inside the app. The reimbursement of any expenses is also automated with the bill’s verification using smart AI/ML intelligence loaded with data on part’s health and historical events.
In the future,
1. Maps and other essential apps will be right on the front dashboard of the scooter for easier navigation.
2. The dashboard will be cloud-connected and show real-time wallet balance or other promoted items relating to the current location or the destination.
The advancements in technology have not only made the commuter’s journey seamless and contactless but also improved the backend operations of companies. E.g., constantly monitoring vehicle parts’ health, timely servicing alerts based on predictive maintenance algorithms, and sending alerts to the support in case of improper usage or theft.
The future of the two-wheeler industry:
The IoT device is currently installed separately by private companies on the scooter. This retrofitting of the device and its associated sensors is inefficient and expensive.
But as we advance, many OEMs would be considering integrating IoT into the scooter. This will transfer the responsibility of manufacturing & installing these devices to the OEM and significantly cut costs for rental companies.
Two-wheeler insurance will become more intelligent and user specific. Users with a good track record can get a discount on ride insurance.
Using Tiny-AI to run ML models on the phone or IoT of the vehicle directly – we can now do on-the fly real time computations of driving patterns, Face or Voice detection in vehicles. New feature set and endless applications are on the way.
The future of the two-wheeler industry is electric:
Most companies are considering a switch to e-scooters to optimize their fuel costs, frauds & hassles. Also, a big step towards creating a sustainable future.
Continuously measuring the behavior of specific parts of EV can also help predict & thus avoid potential failure of most parts of the scooter. Those potential issues can be detected before time, and the support team can be alerted to replace the affected parts.
EV’s motor-driver will have the intelligence to detect whether it is a single person sitting on a bike, or two persons, or a person with a hefty delivery bag.
Every electronic part will have a UID, and it will be easy to maintain inventory and replace damaged parts. This can also detect and report the use of unauthorized spare parts during EV servicing.
By going electric, with a self-balancing variant, even automated delivery of an e-scooter to a user’s location may not be a big challenge.
Vehicles of the future will have parental control to define clearly the max speed, locations allowed to travel, even routes can be enforced if required for safety. Also, moving to EVs will give electronic control of the scooter’s speed to the AI/ML algorithm, and hence city speed limits can be enforced better on the riders.
Apart from the above couple of ways, innovative use of AI / ML / IoT holds the potential to bring thousands of other benefits to the micro-mobility ecosystem, especially to two-wheelers.
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