AI in Transportation

AI in Transportation All Set to Redefine Urban Mobility

The hypotheses and developments in artificial intelligence stirred all kinds of hypes around this field of study. Research is underway for decades but it was only in the recent years that developments managed to hit consumer markets with integration in a range of products and services. AI in transportation is making a huge impact as computer vision software systems and machine learning algorithms are entirely redefining urban mobility.

Many new concepts would make to the development phase while a number of extensively tested features would be available for commercialization. This articles exclusively states the AI innovations that have the potential to revolutionize the industry in 2020.

Use of AI in Transportation for Autonomous Vehicles

Autopilot in aerial and marine vehicles is around for over a century now. Initially, the technology assisted human pilots in a very limited selection of tasks but improved over the time. We have witnessed a number of entirely autonomous aircraft models popularly known as unmanned aerial vehicle (UAV).

However, it was not until early 1990s that we started having autonomy in vehicles – that too on an intensely limited scale. Mitsubishi is arguably regarded as the first manufacturer to introduce and commercialize cruise control in vehicles. Mercedes-Benz is also one of the earliest automobile makers to invest in autonomy.

Society of Automobile Engineers (SAE) introduced a standard to classify the autonomy levels in commercial automobiles. Cruise control – the ability of a vehicle to maintain its lane and issue warning when a nearby vehicle or another object approaches dangerously near – defines the level 1 of autonomy. The standard also defines level 0 where vehicles are only capable of issuing warning and have no other control whatsoever.

The subsequent three levels further classify AI in transportation. Level 2 vehicles are capable of switching lanes and tackling nearby objects without human assistance but driver is required to keep hands on the wheel at all times. Level 3 allows hands off the vehicle but signals to intervene as needed. At level 5, a vehicle is fully autonomous eliminating human driver’s assistance.

SAE Autonomy Levels

Where does the autonomy in transportation stand today?

The challenges in autonomy are more of a regulatory framework than technical limitations. A number of manufacturers including BMW, Nissan, Tesla, Alphabet, Mercedes-Benz among others claim to have developed sufficient technology for self-driving cars. However, each of them is testing the vehicles under a wide range of circumstances. Besides, they are also ensuring to test the vehicles for a predetermined number of miles to achieve more certainty.

Waymo – a subsidiary of Google’s parent Alphabet – is offering level 4 autonomous taxi rides in Arizona. Tesla aims to introduce fully autonomous vehicles by the end of 2020 indicating a giant leap for artificial intelligence in transportation industry. Uber is testing level 3 and level 4 autonomous vehicles manufactured by Volvo. The ridesharing giant in partnership with some automobile manufacturers is aiming to introduce its flagship self-driving car in 2020.

Learn about some of the case studies at Mob Inspire

The year ahead is set to yield the outcome of the efforts building up for the past couple of decades regarding the association of AI and transportation. Although the large-scale commercialization of self-driving cars is still unlikely, yet technology would see widespread acceptance in various parts of the world.

Mobility as a Service (MaaS) to Enhance Ride-hailing Operations

Mobility as a Service

On-demand taxi service providers have redefined the ride-hailing industry by enabling passengers to instantly book a ride with only a few taps on smartphones. Although radio taxi services prior to the advent of on-demand economy were also providing instant booking over phone calls, yet the on-demand model carries its significance in that it allowed passengers and administrators to track ride in real time.

Besides, customers have the power to pay e-wallet and share feedback as soon as ride ends. Similarly, the apps on driver’s end provides them with the best route to destination. Many ride-hailing businesses allow drivers to find the nearby drivers from same service so that they may relocate to a nearby location where they have greater chances of getting a ride request.

Also read: Use Cases of IoT in Logistics

Ride-hailing is not immune of challenges though. Use of AI in transportation is on its way to address those challenges. A number of problems some of which are stated below have emerged in the decade down the road since the start of Uber era.

  1. Number of vehicles and gig workers registered with ride-hailing businesses is growing rapidly.
  2. Number of privately owned vehicles is not reducing as previously aimed.
  3. Service providers are ending up increasing fares to make their businesses sustainable.
  4. The amount of traffic congestion is increasing with dozens of ride-hailing businesses operating.
  5. Bus-pooling is an alternative but most passengers have to walk excessively to hop on a bus.
  6. Ridesharing or bus-pooling also takes more time than on-demand taxi services.
  7. There are very sharp tradeoffs when deciding between on-demand taxi and ridesharing.
How MaaS tackles the challenges of ridesharing with application of AI in transportation

MaaS also referred to as shared mobility network is a concept that has been widely regarded to define the future of AI in transportation. Instead of providing separate services for on-demand taxi and ridesharing, MaaS providers aim to combine these services so that passengers have more seamless experience.

For instance, a passenger looking to travel from point A to B would be offered the most optimized options that would include on-demand taxi, rideshare, and micromobility services. The resultant ride plan would reduce the walking time to almost minimal and may include one or more types of vehicles. A passenger may get a set of options like the one below.

MaaS AI in Transportation

It is notable that passengers would not require to book each ride separately. Instead, the artificial intelligence in transport system would enable passengers to get the entire ride plan by scheduling only once.

Also read: Technology in Logistics 2020

The transport departments in many developed countries are facilitating the efforts to phase out private vehicles, standalone services for on-demand taxi, public transit and micromobility and replace them with shared mobility. The regulatory framework for this transforming is under development stages for the past few years. It is highly likely that MaaS services would attract a large-scale adoption in 2020 in various metropolises.

Facial Recognition for Gig Driver Verification

Facial Recognition Software AI in Transportation

Uber recently faced a ban from operating in London – one of its biggest markets – on grounds of failure to prevent unregistered drivers from using accounts of other drivers. Uber, Lyft and other major ride-hailing businesses previously introduced a number of measures when the city’s transport authority warned ride-hailing giant of a potential ban in case of failure to meet the standards.

The measures include:

  1. Snap selfies at various times during the course of operations to ensure that the driver is a verified one.
  2. Panic button that allows passengers to call 911 with only a couple of clicks.
  3. Sharing ride-location in real-time with one of the contacts.
  4. Reminders to confirm number plate and driver as the one appearing in app.
  5. Automatic alert system to alarm passenger if ride goes excessively off track.
  6. Extensive background checks and driver education before registering them.

Despite all these measures, the ban of Uber indicates that transport authorities are all set to come down hard on ride-hailing service providers. Artificial intelligence solutions in transportation are enabling ride-hailing startups to overcome this challenge. All ride-hailing businesses will aim to add facial recognition feature to verify driver by at most end of the Q2 in 2020.

Mob Inspire is one of the pioneers in commercial development of facial recognition for gig drivers thereby expanding use of AI in transportation. One of our clients in Australia recently requested this feature. We developed and delivered a comprehensive system that recognizes drivers based on Computer Vision technology.

AI for Vehicle Surveillance and Traffic Forecast

Vehicle surveillance with AI in Transportation

Surveillance cameras are being used in hundreds of cities exclusively for surveillance of vehicles. The authorities retrieve the pictures from a particular time of the day to identify crime suspects.

Computer Vision technology is an impressive application of AI in transportation that identifies license plate in a picture to allow characters reading. Mob Inspire uses a combination of Computer Vision algorithms along with image processing to find a license plate in an image that may have any number of objects apart from vehicles.

Once the license plat is found, the algorithms of optical character recognition (OCR) are used to read the characters on plate. The outcome is compared with the database of vehicle registration departments to determine the origin and owner of vehicle. This way, authorities keep a track of each vehicle that passes through any junction in the city.

Artificial intelligence in transportation industry is also enabling transport departments to craft effective projections for traffic. Intelligent systems can identify growing traffic at one road and reducing at another in real-time. They use this information to attach bias in traffic signals so that each driver may get more or less equal wait time.

The use of big data with AI augments the capabilities of intelligent software systems. Traffic management units perform predictive analytics to identify the capacities of roads at usual times and during blockades. The proposed shared mobility network would also integrate passengers by sending them real-time notifications on traffic and recommendations for their route plan.

Drone delivery and AI powered network control system

Drone Delivery Network

Ground based on-demand delivery has been a huge source of relief to consumers’ lives who can deliver and receive parcels at their doorstep within an hour of placing the order. However, the excess of delivery businesses is going to make the space saturated in future. We already witness some cities reeling from traffic congestion.

Research in the past couple of decades indicates that mini drones are highly effective for delivery in urban areas due to growing congestion. Some drone delivery startups have emerged over the past few years mainly in San Francisco and Los Angeles. The operations from these businesses are so far so good.

However, there would be challenges in future as the number of drone traffic would increase. In a conventional case, the administrators will have to define speed, height and path for each drone in a spatial region.

Also read: Impact of Blockchain in Transportation

This is where Artificial intelligence solutions would be vital. Drone based delivery would serve little purpose if operators have to control each drone manually. AI enables you to make the entire delivery process automated from the time a drone is loaded with a parcel, delivered to destination, and returns. This is one of the most notable cases of future of AI in transportation.

The developers at Mob Inspire take their inspiration for drone delivery network from air traffic control systems. The difference lies in the fact that airplane pilots and UAVs set their path as per the directions from ground-based controller whereas drones in an AI network make the route plan independently unless explicitly tasked. A drone can set the height, speed and all notable parameters itself by identifying all other drones in the network.

Drones based on-demand delivery services are emerging for the past few years and 2020 would witness their expansion on a significantly large scale. The year would also possibly bring a regulatory framework for this industry.

Prepare to Live Ahead

The industries associated to transportation including logistics, delivery, ridesharing and automobile are all set to incorporate large-scale changes. Businesses are testing innovative features to enhance operations and optimize costs for years. The year 2020 will transform these industries with the innovations shared above as administrations are finalizing the corresponding regulatory framework.

It is about time you plan ahead of competitors and become of the pioneers in providing these features of AI in transportation. This investment is not only going to facilitate your customers but enable you to minimize costs and time consumption significantly.

Mob Inspire carries an experience spanning over a decade in developing intelligent systems. Our widespread clientele leads their respective industries by utilizing our transportation solutions.

What are you planning to accomplish? Do you intend to optimize your business with matchless software infrastructure or redefine business model right from scratch? Mob inspire can assist you in crafting a business model and developing a highly efficient software solution customized to your business needs. Contact us today so that our experts can take you further.

applications of artificial intelligence

Dubai Launches AI based Virtual Fatwa Service

Dubai ranks among the metropolises that are quickest to adopt advanced technologies. The administration has launched AI based fatwa issuing service earlier this week to instantly respond to religious queries. This development is seen as one of the landmark applications of artificial intelligence.

Fatwa is a formal ruling in Islam issued by qualified clerics in response to an inquisition. Islamic Affairs and Charitable Activities Department (IACAD) is the official body in Dubai to issue fatwas for the past fifty years.

The city serves as one the top destination for companies intending to test their product and services. More businesses are making their ways into the city because Dubai provides a highly favorable environment for corporate activities.

How does AI Fatwa service work?

The inquisitors can access the service at the website of the IACAD – one of the oldest state-run agencies in the emirate. A chat box opens up upon clicking the icon placed on the bottom right corner labeled “Chat With US”. This chat icon is accessible from every page on the site.

Once clicked, a couple of messages appear with Islamic greetings followed by the request to choose language. As soon as you select the language out the available choices including Arabic and English, another group of messages appear stating the topics on which the questions can be asked. The instructions confirm that the service answers questions in four categories including Prayer, Zakat, Purity, and Worship.

AI Fatwa 4

Moreover, one of the messages admits that the answer might be erroneous in some cases and invites inquisitors to assist the IACAD if one finds an error.

Mob Inspire team members tested the services with varying inquiries from the indicated topics. The chatbot responds to each query by mentioning “I understand what you are asking for” if it understands the question. Otherwise, the bot responds with “Sorry could not understand your question, Kindly would you rephrase your question in order to serve your demands properly”.

One of our team members inquired about an ambiguity that he said was facing for quite long. The screenshot showing inquiry and the response of artificial intelligence fatwa issuing chatbot is shared below. The inquisitor believes that this AI fatwa service is highly efficient and shares the most relevant responses to each question.

AI Fatwa AI Fatwa 2

Part of a Larger Plan

The objective of Dubai administration is to make the metropolis the “smartest city” in the world by incorporating artificial intelligence services in all public departments. AI Lab is one of the ambitious programs in this direction. The purpose of this lab is to instantly facilitate residents and visitors of the city.

AI Lab has launched multiple initiatives including startup support to provide a testbed to technology enthusiasts as well as notable manufacturers. The lab also aims to make every government department paper-free by 2021.

In a bid to make Dubai the happiest city on planet, this state-sponsored AI Lab is using machine learning technology to predict the needs and desires of residents and visitors and provide them a personalized and efficient experience that corresponds to everyone’s requirements.

Dubai 10X is another major program to set forth the technology future of the city. This program aims to push Dubai 10 years ahead of rest of the world with the application of advanced technologies including AI, big data, blockchain, IoT, and extended reality. The initiative of issuing Virtual Fatwa is also a part of this larger plan.

Past Applications of Artificial Intelligence in Dubai

The Virtual Fatwa service is claimed to be the first initiative of its kind in the world to use artificial intelligence for religious purposes. However, Dubai is demonstrating the applications of artificial intelligence for over five years.

Dubai Police introduced Robocop – a police robot – that detects emotions and understands gestures of people. The robot is capable of determining the mood of people by reading face expressions and body language.

The Federal Authority for Identity and Citizenship – the official body to recognize citizens in Dubai – leverages AI to serve customers. Multiple other state departments including Dubai Municipality, Dubai Metro, and Roads and Transport Authority are utilizing robots that are powered by artificial intelligence.

Healthcare is one of the earliest sectors in the city to have adopted AI. State-run hospitals are performing cardiac surgeries since 2014. The healthcare administration is also investing in developing artificial intelligence solutions that can efficiently diagnose a disease and make the most suitable recommendations.

The Road Ahead

Dubai presents one of the best robotic process automation success stories in the world. While Virtual Fatwa is apparently one small step, it reflects a giant leap toward building the smartest city on planet.

Mob Inspire is one of the primary stakeholders in the global developments concerning artificial intelligence. Over the past 11 years, we have developed a range of intelligent software systems including shared mobility ecosystem and on-demand solutions. Our artificial intelligence solutions are revolutionizing the world by facilitating users with cost and time optimization.

Contact us today if you are interested in developing AI solutions or to incorporate robotic process automation in your department.

Artificial intelligence in agriculture

Use Cases of Artificial Intelligence in Agriculture

The agricultural practices over the decades have seen a remarkable transformation. Innovations of information technology and, particularly, artificial intelligence in agriculture are ensuring that agriculture sector provides impressive business opportunities. Volume of production, ease of monitoring, cost of farming, and operational comfort are some of the benefits that AI brings in agriculture.

Following are four of the most notable use cases of artificial intelligence in agriculture.

    1. AI for Harvest Improvement

    The use of excessive herbicides and pesticides do not only reduce the production volume of crops but also affect quality. Therefore, plant pathologists are leveraging the power of AI technology to optimize production by controlling the amount of chemical substances. Consequently, the quality of harvest is significantly enhanced over the past few years.

    To achieve this feat, IoT-based devices aid AI software to decide the areas which require the use of herbicides. Besides, this combination of software systems also assists in suggesting the precise quantity of herbicides above which the yield would start to decline.

    2. Robotics in Agriculture for Soil Quality Tracking

    The assistance from drone cameras powered by computer vision technology allows farmers to identify regions in farm which need attention. This technology enables farmers to perform surveillance of area in real-time. Besides, drones and the associated technologies reduce the amount of time required to monitor entire land area.

    The statistics below indicate that number of people employed in agriculture is decreasing rapidly owing to successive industrial revolutions over the decades. Before the requisite technologies, farmers had a hard time coping up with this change.

    Fortunately, research and development in robotics have changed the circumstances in favor of agriculture. Now, the producers can attain much more ambitious production targets in the same land area with a fraction of workforce.

    3. AI-based Risk Analytics

    The efficacy of risk assessment defines the quality of farming. You need to identify all the possibilities leading to losses and the potential volume of loss in each case. Former is the quantitative risk assessment whereas latter is qualitative one.

    Role of artificial intelligence in agriculture highlights the most while crafting and executing a risk assessment strategy. The AI systems assist in predicting weather months ahead. This ability comes in handy in areas which are more likely to receive excessive rainfall and subsequent floods. The land owners can plan if the flood is likely or not and if it carries the potential or not to inflict damages to crops.

    4. Predictive Analytics for Aggregate Planning

    The utilization of data analytics is significant in contemporary agricultural practices. Data analytics enable farmers to make effective aggregate planning. In essence, farmers can plan the amount of production which should be stored after milling and the amount which requires to be sent to retailers immediately.

    Most of the crops cannot be stored for longer periods without spending excessive money on expensive storage schemes. Artificial intelligence in the field of agriculture assists in developing an appropriate balance between demand and supply. Farmers often find it challenging to deal with task practices that they have not performed earlier. AI chatbots are addressing these challenges effectively by providing instant assistance to farmers’ queries.

Artificial intelligence is becoming an essential component in modern farming. Farmers are able to attain significant advantages by reducing costs and increasing yield. Would you like to incorporate AI systems in your farming business as well? Contact us so that one of our experts will develop business use cases specific to your business.

Leveraging Power of AI for Small Business

Artificial Intelligence is buzzing our ears for more than five decades now. However, the field started to bring value to businesses at the start of the 21st century. With time, small businesses also began to leverage from the power of AI. Unfortunately, many SMEs still carry the perception that AI for Small Business is unrealistic.

Busting Some Old-school AI Myths

Two decades of significant development makes AI as powerful for small businesses as for larger ones. Business owners and managers not incorporating AI usually present one of the following reasons.

AI is reserved for Large-scale enterprises

One can perform more activities with AI then a transistor in a modern computer. Unlike this transistor metaphor, the results are not bad at all. Small businesses can address challenges and equally leverage the AI benefits as large ones.

Deep learning, an approach to AI, is limited to companies with massive volume of data at their disposal. However, one does not necessarily have to perform expert data analysis to use AI.

Both SMEs and large enterprises can use machine learning. Besides, they can also use automation tools to spend resources of time and money in more effective domains.

AI is complicated to learn

Some small business owners carry the perception that AI software is complicated for them to learn. This notion was correct until some five years back.

However, AI has seen a drastic development since then. The communities of volunteer programmers and companies are performing a tremendous job for mainstreaming of AI.

Now, SMEs can acquire AI tools and pre-coded templates for achieving a number of tasks. Moreover, a user does not have to care about the backend functionality. Instead, they can use a nicely-built interface to accomplish a range of operations.

AI has nothing to offer to my business

If your company has a website or mobile app, the AI can help big time irrespective of the scale. In essence, it will cut down the costs being spent on ineffective marketing and excessive workforce.

Small enterprises do not need to employ AI experts for fancy salaries. Instead, they need to find out the appropriate tools which can assist in automation of their businesses.

Following chart demonstrates the response of survey participants upon asking about their expectations from AI. High interest of businesses toward saving time and money and acquiring useful information push researchers to work in these areas. Consequently, the AI tools help businesses of each scale.


How can AI Help Small Businesses?

There are multiple ways in which AI assists small businesses in smooth running of operations and to increase profits. Following three are the most effective and widely used ones.

1. Boosting Customer Service Management

The web allows companies to run their businesses remotely from anywhere. Although this ability enables them to expand global outreach, yet intensely varying time-zones are existential threat.

A customer seeking services at daytime in the US is unlikely to get a response from a company located in Asia or Eastern Europe. Absence of response will prompt the customer acquire services from another company.

There are two exceptions where a company can engage customers during off hours. First is to keep a sales team which works odd night shifts. Second and the most appropriate solution is to engage the visitors with chatbots.

Chatbots are intelligent software systems integrated into web and mobile-based apps and AI Applications for Small Business. They can answer advanced as well as basic queries. Chatbots are particularly helpful to engage customers while a human attendant is away.

Over time, the development in AI enables the chatbots to improve their performance incredibly. The current degree of intelligence allows bots to chat as good as their human counterparts.

Moreover, the trust in chatbots is increasing over the time. Only 30% of respondents of a survey reported apprehension that a bot would give wrong answers. Just a few years back, this number was significantly higher.

2. Marketing in predetermined Dimension

Marketing is one of the principal areas where AI Tools for Small Business are making their mark. It is enabling the business owners to cut down marketing costs remarkably by running targeted campaigns.

A decade back, marketers had to run hit and trial methods to attract potential leads. Since their advertisement was not a directed one, most of the people seeing the ads were irrelevant.

Today, Facebook, Twitter, and Google apart from other social networks and search engines enable marketers to reach relevant audience. Although these companies advise the advertisers to enter details about targeted demographics, yet their AI algorithms make impressive effort too.

The objective of these algorithms is to find similarities between demographics. Facebook calls these similar groups of users as “Lookalike Audience.” Thus, small companies can climb above their competitors by leverage of integrated AI algorithms.

Besides advertising, the AI for small business marketing reflects in tools including Marketo, HubSpot, and MailChimp which perform the tasks of days in minutes.

3. User Modeling and Predictive Analytics

It is highly assistive for companies to be able to find the path which brings customers to choose their services. Regardless of the volume of business, owners can align their efforts toward effective directions.

Whether you are an e-commerce store owner run a small food delivery business, AI brings remarkable efficiency to your business.

In either of the above examples or another online business, predictive analytics assists your customers in decision making. The machine learning algorithms make predictions about customers’ choice and suggest them accordingly.

For instance, a delivery business recommends food outlets and kinds of food based on customers’ previous searches. Moreover, delivery agents can find the shortest route to destination since machine learning enables them to determine distance and traffic volume on various roads.

The companies can collect legitimate data of customers and run simple queries on data with pre-developed and pre-configured tools. These tools, for instance, Microsoft Azure ML, Google Cloud AutoML, and a bunch of others do not require technical expertise. Users with basic AI knowledge can use these tools too.

Do you also want to integrate AI in your business to perpetuate growth and profits? Contact us today to allow our experts suggest you the most effective AI utilization tailored to your business needs.