How AI & IoT Are Making Shared Mobility More Efficient

The integration of AI and IoT is driving the development of autonomous vehicles, which have the potential to revolutionise the shared mobility industry.

AI-powered chatbots for customer service are becoming increasingly popular.

Source : Getty

By Narayan Mishra

The advent of artificial intelligence (AI) and the Internet of Things (IoT) has revolutionised the way we live and work, and the shared mobility industry is no exception. Shared mobility services, such as car sharing, bike sharing, and ride-hailing, are rapidly evolving with the integration of AI and IoT technologies, leading to enhanced efficiency, safety, and sustainability, as well as creating new opportunities for businesses and consumers.

Efficiency gains are being realised through the use of AI and IoT in fleet management, customer service, and cost reduction. 

AI algorithms can analyse large volumes of data collected from IoT devices, such as vehicles and sensors, to optimise fleet allocation, routing, and maintenance. These algorithms can predict demand patterns, optimise vehicle availability and utilisation, and reduce idle time, resulting in more efficient operations and improved profitability for shared mobility service providers. 

AI-powered chatbots for customer service are becoming increasingly popular, providing instant responses to customer queries and reducing the need for human intervention, leading to improved customer satisfaction and reduced operational costs.

IoT devices are also improving safety in shared mobility. Connected vehicles with IoT sensors can collect real-time data on speed, location, and driver behaviour, which can be analyzed by AI algorithms to identify potential safety risks, such as harsh braking or speeding. This data can be used to provide real-time feedback to drivers, encouraging safer driving practices and reducing the risk of accidents. IoT sensors can also monitor the health of vehicles, detecting maintenance issues before they become major problems, thus improving the safety and reliability of shared mobility fleets.

Sustainability efforts are also being enhanced by the integration of AI and IoT in shared mobility. Shared mobility services already promote the efficient use of vehicles, reducing congestion, air pollution, and carbon emissions. However, AI algorithms can further optimise vehicle routing to reduce empty trips and minimise fuel consumption, leading to a more eco-friendly operation. IoT devices can also monitor vehicle emissions in real-time, allowing shared mobility service providers to take proactive measures to reduce their carbon footprint, such as using electric or hybrid vehicles, implementing eco-driving techniques, and managing charging infrastructure more efficiently.

Moreover, the integration of AI and IoT is driving the development of autonomous vehicles, which have the potential to revolutionise the shared mobility industry. AI-powered autonomous vehicles can navigate, park, and communicate with other vehicles and infrastructure using IoT technologies, leading to improved safety, efficiency, and user experience. For example, autonomous vehicles can communicate with traffic management systems, traffic lights, and other vehicles to optimise traffic flow and reduce congestion. They can also provide personalised services based on user preferences, such as adjusting the temperature, lighting, and entertainment options inside the vehicle.

Despite these benefits, there are challenges and concerns that need to be addressed in the integration of AI and IoT in shared mobility. Data privacy and security are major concerns, as the vast amount of data collected from IoT devices raises concerns about the privacy and security of user information. Shared mobility service providers need to implement robust security measures to protect user data and prevent unauthorised access. Ethical implications of using AI in shared mobility, such as biased algorithms that may result in discriminatory practices, also need to be addressed. Ensuring transparency, explainability, and fairness in AI algorithms used in shared mobility is crucial to ensure equitable services for all users.

In conclusion, AI and IoT technologies are reshaping the shared mobility industry, leading to enhanced efficiency, safety, and sustainability. However, addressing challenges related to data privacy, security, and ethical implications of AI is essential to ensure the responsible and equitable integration of these technologies in shared mobility services. With the advancement of AI and IoT, transit app, live tracking app, public transport app, trip planner, and real-time live tracking app are becoming essential keywords in the shared mobility industry.

(The author is the Co-founder and CTO at Tummoc, a public transit app)

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