The usage of sensors in autonomous vehicles is made possible by big data. An autonomous vehicle won’t be useful on the road if it doesn’t have access to a consistent and dependable flow of huge data about self-driving cars; it won’t know what to do with the data it collects. Without data, a connected car is analogous to a child who doesn’t know better and puts their fingers in electrical sockets, grabs a knife, or tries to catch a spark.

Big Data serving Big!

Nearly every business has seen a change, thanks to big data. From more overtones, like media and advertising, where it’s used to forecast trends and analyze audiences, to more covert ones, like healthcare or energy management, where a lot of data is utilized to explore the largest difficulties we currently face. When it comes to big data, its analytics, and IoT, the automotive industry is not an exception. They are employed in numerous stages of the production and promotion of automobiles. However, investing in the creation, testing, or use of autonomous vehicles is undoubtedly the most innovative thing automobile firms can do with their massive data.

One of MarketsandMarkets’ first comprehensive analyses on automotive AI businesses predicted that by 2025, the market value of this sector would be USD 10 billion. Even larger figures have been shown by more recent statistics. For instance, analysts at Global Markets Insights (2019) forecast that by 2026, there will be a rise from USD 1 billion in 2019 to USD 12 billion. It appears to be a safe investment because the majority of significant IT corporations and significant manufacturers are confident in the unavoidable success of such cars.

What change does big data make?

To position the car on the road and keep it in the right lane, we use sight to notice the traffic signal switches and spatial awareness. To judge how close other vehicles are, we use sound, and to remember a traffic sign, we use memory. In addition to being able to process, train, and learn from errors, engineers want AI to comprehend each of these processes when creating an autonomous car.

As huge data is necessary for autonomous vehicles to function, so are sensors that collect this data. Driving involves the utilization of a variety of senses and sophisticated cognitive processes, sometimes without our awareness. An autonomous car uses different types of sensors to see and feel the world around it like a camera, radar, and lidar etc.

In a matter of milliseconds, an autonomous vehicle processes and analyses data from a variety of internal sensors. This enables the car to safely go from point A to point B while also transmitting information about the road’s state to the cloud and, consequently, to other vehicles. Then, other vehicles are given access to massive data from self-driving automobiles.

Big data Into Action!

Do you think smart cars simply use the data they collect for themselves? Think again. This data’s actual potential is substantially higher:

• An automaker may detect a problem with your automobile from a distance and notify you right away through your car.
• The management of a fleet of hundreds or thousands of linked vehicles can be made more effective and efficient with the use of vehicle data.
• From the gas stations that drivers select to the music they listen to, big data is a rich source of behavioral insights. Customer service, sales, and marketing all benefit from having this knowledge.
• Big data from linked automobiles will improve the accuracy of city planning and engineering; examples include more effective road planning, early warning systems on risky places, and safer pedestrian crossings.
• Big data from linked automobiles can be used to create insurance plans for drivers that are specific to their behavior

Conclusion

Without big data, the automotive sector cannot advance further. The usage of data by cars will be analogous to the use of gas or energy in the connected and autonomous vehicle future. Companies need to have experience in the automotive sector as well as knowledge of AI, machine learning, natural language processing, IoT, and platform development in order to offer big data solutions for the sector.

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Research proves that 95% of companies are investing in IoT since it will help them improve their sustainability practices as well it is also the backbone for many solutions in the present and future. IoT solutions such as real-time tracking, route optimization, predictive asset, and product maintenance can help increase sustainability and productivity. According to Gartner the aviation and transport industry will account for the largest opportunities to increase and generate $64 and $11 billion by 2028 with the help of IoT features. Implementing IoT approaches for different segments of the transport industry such as sensors on railways, highways, roads, bus stops, airports can smoothen the entire operation process as well as increase visibility and transparency.

Air travel
The use of IoT not only provides passengers with real-time information about their baggage and boarding details but also helps reduce excess waste and utilize energy and power in a sustainable manner by switching off lights in empty areas and controlling the temperature.

Public transport
IoT technology not only updates passengers with real-time data about the bus schedule and timings but also reduces wastage of fuel, resources, materials, and cost with its real-time and automation features. IoT sensors are beneficial since they provide data about real-time air pollution as well as reduces pollution. Moreover, the sensors help address issues regarding temperature, fuel, and route optimization.

Road traffic department
The use of IoT helps in managing the road traffic department in an effective manner. The real-time features help in managing traffic, accidents, and roadblocks. It helps with parking issues and also helps individuals in identifying where they parked their cars to avoid wasting time and fuel.

Supply chain
Implementing IoT with supply chain strategies for companies has proved to be effective and efficient since it helps in reducing waste, fuels, and costs. It even smoothens the transport solution process with its real-time features and tracking devices. It even minimizes the usage of electricity.

Logistics
This sector accounts for 1.6 billion of CO2 emissions. IoT technology can be used to improve communication, usage of resources and materials, and navigation. The real-time feature will help drivers to avoid routes where there is a lot of traffic or delay which will reduce wastage of fuel. Better navigation due to real-time data will help minimizing harmful emissions. IoT data can help update owners regarding maintenance issues such as faulty parts which can reduce waste. IoT is a great way to minimize the use of power and electricity due to its smart features, real-time data, and sensors.

Automotive Industry
The connected vehicle technology enables communication among vehicles and infrastructure which can reduce crashes, energy, and gas emissions with the help of real-time and navigation IoT features. It even improves customization and the complete fleet operation becomes much more effective and efficient since it reduces gas emission and fuel.

The advantages of integrating IoT practices with day to day operations

IoT technology is beneficial not only for the present but for the future as well. It helps increase effectiveness for different operational activities at a low cost. Not only does it help with sustainability but also increased the security of different stored information.
PwC states that technologies such as IoT can help reduce environmental challenges and increase sustainability.

Sustainable environment – Real-time data and sensors help in better route optimization, planning, understanding traffic issues as well as reducing fuel, wastage of resources, and energy.

Smooth operational practices – Real time data enhances the entire operational process. It helps reduce cost and improve productivity and monitoring.

Better customer experience – Increases focus on customization as well as with real time data customers can plan better. It increases transparency, communication, and efficiency.

Increased safety and protection – With the use of sensors, important aspects such as temperature, speed of vehicle, issues and accidents can be minimized. It helps improve the safety of various aspects of the transportation industry. Helps understand key issues regarding maintenance.

Cost effective and efficient – IoT sensors and real-time features help improve planning when it comes to resources. Sensors help with sending updates regarding maintenance to avoid any accidents or wastage of resources. It even reduces energy consumption.

In conclusion

Nowadays, both businesses and consumers focus on sustainable practices which is why integrating IoT along with the day-to-day operations and goals of the company can increase sustainability and improve the carbon footprint in a cost-effective manner. The adoption of IoT technology by companies will help reduce emissions, pollution, and fuel, which will indeed make the world a better and greener place for the present and future.

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Quantum computing has a variety of applications in revolutionizing the automobile industry such as improving battery performance, avoiding traffic congestions, preventing car accidents and mishaps by machine learning and analysis etc. that can greatly benefit the sector when they come to fruition. Machines in quantum computing work with physical properties of matter, such as superposition or entanglement, which means that calculations can be performed on multiple states of matter at the same time, drastically reducing computation time.

Advantage of Quantum Computing The brainchild of Nobel laureate Dr Richard Feynman, quantum computing has progressed to enormous levels of growth, finding a variety of applications in different fields and sectors. Quantum computing involves simulation of the physical nature of objects at subatomic sizes while allowing them to exist in more than one state. This allows rapid simulation and processing of data than conventional systems, making quantum computers much more powerful, efficient, and faster. It has been applied in fields like Cryptography, Medicine, and material sciences to accommodate multiple variables or molecules in simulations to reach the desired end product or solution. Various automobile companies like BMW (CNET) and Hyundai (Eetasia) have started working with quantum computing systems to solve various issues like cost optimization, development of new batteries, optimization of components to improve cost-effectiveness etc.

Quantum Computing in Battery Technology

Quantum computing has been applied to develop effective solutions in improving the battery technology in cars and automobile systems as it can simulate multiple molecules of compounds simultaneously in different states, conditions, and environments to help identify the ideal combination of variables. Hyundai Motor Co. has partnered up with quantum computing experts to develop a robust battery that can function with improved capabilities and durability when used in electric vehicles. They aim at reducing the cost of battery development and production to reduce the overall cost of the vehicles, improve affordability and progress towards sustainability. A quantum computer of sufficient complexity—for example, enough quantum bits or “qubits”—could theoretically achieve a quantum advantage, allowing it to solve problems that no classical computer could ever solve. In theory, a quantum computer with 300 qubits fully dedicated to computation could perform more calculations in an instant than the visible universe’s atoms Quantum computing has also been applied in the development of novel technologies that can improvise the functioning of EV batteries by incorporating advanced technologies to cool them. It is applied by compartmentalizing big issues into individual parameters that are simulated using quantum computing to be later integrated into the conventional systems as a hybrid model or to fashion a completely new model by combining the solutions offered by quantum computing(EENewsEurope).

Quantum Computing in Autonomous Driving Quantum computing can facilitate the design and development of powerful operating systems to produce self-driving cars, simplifying transportation and reducing the chances of human errors in road traffic accidents. Artificial intelligence and machine learning require the real-time analysis of vast amounts of data to produce optimal responses to changing environmental conditions and quantum computing with its excellent computational features

can lend a hand in facilitating the requirements. Volkswagen(Prescouter) has experimented in the design and development of computational systems to optimize traffic control and regulation in the city of Beijing and has found great success in this venture. It also has applications in improving vehicle to vehicle and vehicle to cloud communications in next-generation cars that are expected to have the ability to communicate with cloud computing systems to regulate driving data. This will help in traffic and fuel optimization in cloud-connected cars while providing a safe environment for decentralized communication between them.

Conclusion

Quantum computing has unlimited potential and practical applications across different fields and sectors and can make a path for enormous progress in the automobile sector. Companies and enterprises in the automobile sectors would greatly benefit by working with quantum computing as it is a leap towards greater sales and a greener environment. Recently, quantum computing has gained a lot of traction in both general society and the private sector. Companies have been pouring huge sums of money into quantum computing research, with the last few years being the busiest for this innovation.

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While it has been common for suppliers to stop measuring themselves post the delivery of a product, the emergence of reverse logistics means a new variable in customer satisfaction. Although this is not to suggest that it is a novel aspect of retail – large retail businesses have been managing product returns even preceding the e-commerce era. However, the see-saw battle between various corporations on the said digital platforms necessitates that companies put forward and reverse logistics at par on their priority list. Yet, the simple truth is that many myths and misconceptions cloud executives’ views on strategies for reverse logistics. And even though studies predict phenomenal benefits to ramping up this department, only a minuscule number of companies name it an essential investment.  

Apart from the one obvious reason which is volume: the number of transactions in reverse is usually far lesser that forward logistics. 

Why do retailers continue to let reverse logistics play the second fiddle? 
It is, essential to identify and solve some of the major puzzles in reverse logistics.   

1) Lack of dedicated team  

Most firms do not boast a sole reverse logistics department. It is, many a time, assigned with an underqualified individual/team discrediting its importance as a domain of itself.  However, the Inability to monitor the condition of products returned, percentage of sales lost, customer base lost, secondary revenue loss etc., could break the foundation of your enterprise, especially  if the returned products can be repaired or repurposed, scrapped for parts, or directed to the secondary market.   

2) Categorisation of the returned products as trash   

As cited earlier, this is one of the biggest misconceptions of the modern retail industry. At the same time, less than 20% forms the bulk of all defective returned products; even defective products can find value through proper processing. Analytics has shown that the number one reason customers return items is remorse, not defect. The key to reclaiming value from returned goods, damaged or otherwise, is the implementation of streamlined and effective reverse logistics processing.  

For instance, we know that the reverse logistics chain is initiated the second a customer clicks return on the purchased product. Therefore, the initial assessments must happen at this instant, making an effort to understand the cause of the return to make an informed guess on how it can be dealt with to ensure your company’s losses are minimal.  

3) Absence of tailormade reverse logistics software  

It is appalling how every subsequent point made in this analysis leads back to the others; here, we see the consequences of a common myth in action: ‘managing returns is simpler than running distribution.’ Nothing could be further from the truth. 

 The fact is that  returns management is far more complex than distribution. Returns management requires executives to work with buyers, operations, sales, accounts payable, and systems. While the leadership on the distribution side needs to care only about the safety of their loads as a whole, the reverse logistics manager must inspect every item in detail. In the case of returns, the OEM has to grant authorization before shipping. F 

Most distribution centres employ WMS to expedite these tasks to manage the large volumes, and the returns are synchronously processed through the same software resources. This creates complications because the software is just not designed to hadle the unique workflows and level of detailing required for Reverse Logistics management   

Warehouse management system for reverse logistics  

While your firm’s standard WMS will encounter difficulties in processing forward and reverse logistics, it is possible to build them to maneuver in both operational areas seamlessly.  Much rides on the symbiosis between the WMS and the enterprise resource planning systems (ERP). This combination works in a customer-oriented manner, maintaining what looks like a thorough customer record, complete with the profile of all transactions between the company and the customer. The ERP platforms, paired with a warehouse management system, allow companies to track returns easily, monitor the movement of goods, issue credits through the accounting system, and update everything in the customer record.  

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The current state of Port Management 

While this illustration may project the massive volumes that are the everyday norm in international maritime traffic, the rather mundane management solutions employed by some of the world’s busiest ports do not mirror the stir in the industry; with the majority of ports worldwide classified as Tier 2 and 3 – where operations are primarily manual and modern equipment and resources are slow to come, making these government-owned ports sluggish and stagnant. In an industry like transportation, businesses toil to improve efficiency, even if only by an iota, as they recognize how far it may go in giving them the edge, putting them in the best position to have their competition by the hip. In other words, improved efficiency in maritime transportation translates to immediate positive transformation in the global economy.   

While improved turnaround time and efficiency as a payoff of greater automation seem quid pro quo, it is also crucial in optimizing safety and security. With the current traffic and competition in maritime trade today, port executives must work infallibly to ensure smooth function; slight errors from the employees can lead to a slew of issues, like stalling and even severe accidents owing to carelessness and mismanagement. Therefore, it is as clear as day that apart from infrastructural development, the development of the IT resources and improved automation holds the key to accelerating progress and boosting revenue.   

In an ever-changing environment, which involves operations from various corners of the globe, all with individual maritime policies and regulations, manual management and administration will continue to become more complex with every passing year.  

The power of the Maritime Single Window  

This problem could be resolved if port management were empowered by IT with end-to-end visibility for mariners, improved transparency, and data sourcing through IoT and RFID. Yet, the most tactile feature would be streamlining complex procedures (compliance, safety, etc.) by connecting all the governing agencies and offices through one portal. In addition, it must account for the differences in policies and rules of various countries mandated by the governments of the user.   

Enter the Maritime Single Window (MSW), the portal that makes cross-border trade simpler and marine logistics chains more streamlined, mandated by the IMO in 2019, and yet to see marked adoption rates worldwide. The myopic view of many ports fails to see the harmonization of vessel reporting obligations possible with it and the customs process solutions. We can link the governments involved in direct trade electronically for the first time, providing tangible cost savings for businesses and the government. And for governments, it is easier to check and eliminate corruption by improving methods to counter dishonest practices and reducing discretionary decisions by simply automating them.   

The benefits they offer to both traders and port managers are myriad and can be listed as follows:  

For traders  

• Single submission – With suitable national registration, companies must enter the required information once rather than submit paperwork at every stopover.   
• MSW can take over the clearance procedures as they are facilitators of complete and accurate data to said cross-border agencies.  
• It can win maritime traders higher credit scores from banks, improving their financial positions.  
• More efficient logistics: Companies can get cheaper logistics and transport services because MSWs facilitate services connecting transport and logistics chains.   
• Reduced business transaction costs: Companies can interact with the standard import and export service ecosystem with lower prices and higher efficiency with an MSW. This may reduce the recruitment needs of companies within their international trade staff, thus saving human resources and management costs.  

For Ports & Regulatory Agencies   

• Connectivity, simplification, standardization, automation, and increased reliability of information exchange and data reuse  
• Ease of transactions resulting in lower transaction costs.   
• Facilitation of G2B status information.   
• Improvement of port logistics.   

Future-proofed shipping  

The verdict has to be that MSW is the future of port management and logistics; it galvanizes and bullet-proofs shipping for all parties. It is ever scalable and can be reproduced over multiple ports and their terminals. And while their adoption is straightforward, stakeholders must carefully modify their business strategies to stay clinical amid the changes brought within the system. When implementing the single window system, care must be taken to maintain the legacy systems, information flows, and processes to create a viable trade ecosystem that benefits all parties equally.  

If you wish to transform your maritime business and desire a trustworthy partner in doing so, browse the blackrock website to read about xPort, our pioneering MSW solution. 

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With little competition and a fresh market, this may be the best time to set up an on-demand fuel delivery business, especially in a world emerging from the shadow of lockdowns and the automobile industry seeing a resurgence.   

The Building Blocks 

With the global gasoline/diesel requirements consistently outweighing the capacity of fuel stations over the years, on-demand fuel delivery is bound to be an imperative in the coming years. However, with that said, one must play their cards right at the very beginning, partnering with a reliable IT solutions provider, securing compliance from governmental authorities, and so on.   

The next step must be to build your fleet, equipped with the resources for everything from transportation to maintenance and safety. Businesses must do it with a keen eye on the reasons for the very existence of this market and the audience the firm specifically caters to. For instance, companies must hire HAZMAT (Hazardous Materials) drivers, who are elite drivers involved in the transport of flammable material. Digital Solutions that complement the fleet must also be in place simultaneously (real-time tracking systems, forward-looking camera systems, IoT sensors, collision mitigation technology, and the like).  

It is also vital at this juncture to address the towering safety concerns involved in transporting highly combustible liquids and gases over significant distances by road. The companies must immaculately monitor the transportation tanks to ensure safety; they must appropriately allocate funds to ensure this, without which the company’s existence will perennially hang by a thread.   

Only then must intrepid business owners venture into creating the on-delivery app to enable the service, though last is not the least. The usability shortcomings of the application are hurdles many entrepreneurs fail to cross, with order tracking and route management being the Achilles’ heel in these solutions. The architecture of the app backend is another crucial hallmark as end-users will use the app over data or Wi-Fi all the time. Thus, the seamless delivery operation is staked almost wholly on some key app features that demand discussion.   

Vital features of an On-Demand Fuel Delivery app: 

• Pricing charts  

The customers must get a glimpse of the savings they make through properly illustrated price charts; the introductory offers may be the bait for most customers. However, no compromise must be made on fuel quality, with double-filtered fuel as the norm.   

• Real-time tracking  

Given that the orders for fuel delivery often are in emergencies, the two-way tracking system will be equally valuable to the delivery agent and the customer while also winning the customer’s long-term trust. In addition, they can use third-party maps that show the delivery routes with ETA.   

• Accept/Reject options  

Since safety is paramount in an on-demand fuel delivery service, the fuel delivery agent must have the right to reject orders if they are inaccessible or compromise security in any manner. There must also be an option to keep charges pending until the delivery agent can make an informed decision.  

• Synced with various payment options  

      The customers should be able to make their payments over a broad range of payment methods at their convenience. They must be aware of the various situations the customers may find themselves in and be adaptable to COD, online banking, and the slew of mobile banking apps with whom they must ensure compatibility. There must be an order/transaction history so the users can keep track of their expenditure online.   

• Customer support  

The business must address the fears and misconceptions of their customers by establishing communication channels between the people and expert employees who can mitigate their doubts and create clarity over the ins and outs of the delivery protocols. Automated messages can also have a positive impact in this regard.  

blackrock recently built a digital platform for on-demand fuel delivery for a US-based early-stage enterprise. You can read the complete success story here. 

If you have an idea for a big change in the automotive world and need the right IT support to help you realize it, drop a mail to sales@blackrockdxb.com.  

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The rising costs caused by extra safety guidelines put forward by governments the world over, the sudden changes in their processes owing to these safety guidelines, and dwindling businesses were severe concerns for many key players in this sector. The lockdowns in various countries caused heavy supply chain disruptions, affecting international and intra-national logistics, leading to slowdowns in other related industries. Many small trucking companies in the USA were forced to file for bankruptcy in 2020 owing to COVID, as they lacked resources to turn things around or wait for the pandemic out.

The impact was evident in other industries as well – the aviation industry is one such example. Most of the major routes were either thoroughly grounded or reduced to a few hours of operations due to the lack of the required number of passengers to cover the substantial operational costs. As a result, there was a decline in people preferring to travel to international locations, bringing the demand further down.

The work-from-home situation dragged down the number of corporate travelers, which amounted to 75% of airlines’ profits. In addition, there was a decline in people preferring to travel to international locations for personal reasons, bringing the demand further down.

The global freight forwarding market was also among the most brutally hit, with an expected decline by 7.5 percent in 2020, compared with the previous year. The case was similar for various other transportation companies – a good example would be that of the global cab aggregator, Uber, which saw a 50 percent fall in its gross bookings year over year during the pandemic.

However, after a year of living through the pandemic, the outlook is positive, and the world is adapting to the changes caused by it.

How business leaders should navigate the pandemic to ensure resilience

Even though the pandemic disrupted many transport and logistics businesses, many leaders took this as an opportunity to accelerate their digital transformation journey that could catapult their business to new and sustainable levels.

Optimizing Operations

Business leaders must reassess how their businesses operate and focus on optimizing them to reduce any unwanted costs. For example, transportations and logistics companies bear the brunt of working on legacy processes, and opting to re-engineer them would result in high payoffs. For example, a warehousing business could use analytics and location data to plan various shipments to be loaded and unloaded optimally.

Similarly, airlines can use the data of passenger onboarding, baggage tag scans, or other tracking mechanisms to deploy FTEs to handle these passengers optimally, hence controlling the operational costs even further.

blackrock enabled an international construction equipment manufacturer to develop a comprehensive Fleet Management System for optimizing mine operations. As a result, the project is set to increase its efficiency and operational costs. You can read the news article here.

Providing Transparency

A business must provide transparency to all its stakeholders to make the business process easy, manageable, and measurable. For example, with every lockdown, there was rising consumer demand for home delivery and thus an increased demand for last-mile delivery services. This highlighted the need for automated, contactless delivery technology. TAs a result, these businesses need to build a digital ecosystem to ensure that their customer engagement levels are high and that transparency is maintained throughout their business processes.

Even in a B2B scenario, logistics companies need to ensure that relevant data is available to their customers to ensure their business isn’t disrupted. This is particularly significant in the wake of increased demand for e-Commerce and enterprises supported by transportation and logistics companies adopting such a transition. As for the internal stakeholders, they are improving the visibility within the supply chain, ensuring that they are ready for any disruption that might happen within the supply chain.

A good example of this would be the comprehensive logistics management platform created by blackrock for a global leader in supply chain solutions – you can read the complete success story here.

Harness the power of data

The COVID-19 pandemic has highlighted the importance of leveraging data and analytics solutions to make decisions. While data utilization in transportation and logistics has grown significantly over the past few years, the pandemic has accelerated an urgency to innovate. This led to rising demand for supply chain risk management and real-time monitoring systems during the past year.

With the adoption of multi-modal transportation and technological advancements leading to many different data sources like cameras, GPS, and geo-location, it is a logical step to consider this diverse data ecosystem. This unmatched amount of data can help businesses use advanced data and analytics solutions to enhance operations, reduce costs, and better serve travelers.

Understanding the mobility patterns and transportation and logistics trends early on will give rise to effective risk and disaster management, and those businesses accelerating their digital transformation journeys will reap the benefits in the long term and would be able to tackle any other significant disruptions head-on.

blackrock helped an Indian hill-state tackle its road safety challenges by going digital. You can read the complete story here.

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In fact, McKinsey estimates that these advancements in automation will lead to logistics costs dropping by as much as 40 percent. But automation is not limited to the workflows in warehouses – logistics companies are realizing that they can change the way goods flow across all modes of transportation as well – it can expand a company’s ability to flex with peak demand, pick and pack individual products and take on heavier cargo.

Let’s take a look at the revolutions  automation can cause in the transportation industry:

Autonomous Trucks 

Two-thirds of all goods transported in the United States are moved by trucks, and truck driving is the primary occupation in over half of the states in the USA. But ATs, as these fully automated trucks are called, are about to change all that in the future, with their capabilities of being able to operate without any human intervention. A fully autonomous truck would be able to operate at scale without drivers from loading to delivery. 

While full autonomy is a long way off,  experts in the industry have predicted that the shift will happen in several phases, with each phase bringing in a higher amount of cost-savings than the previous ones. 

They also estimate that it will take around ten years for fully autonomous trucks to get on the road and several more before we can envision a completely driver-free trucking industry nation-wide. 

Port Automation 

Automation in ports has five distinct parts: automated equipment, equipment control systems, the terminal control tower which is the “brain” of the automated terminal, human-machine interactions, and interactions with the port community.

From the first automated port that was set up in Europe in the 1900s, over 40 ports have since installed equipment to automate to some degree. Despite the slow returns on investment that most ports are seeing, they are the ideal candidates for automation – their physical environments are predictable and the activities conducted are straightforward and often repetitive and they generate vast amounts of easily collected data. 

With automation, the safety in ports improves, the number of disruptions caused by human labor reduces and the performance of the port becomes more predictable. Once the initial hiccup of huge investment is overcome, ports become ripe to glean the benefits of automation.  In fact, according to research, successfully automated ports see their costs falling by 25-55% and their productivity increasing by 10-35%.

Automation in Air Freight

With companies such as Amazon making their stakes in the logistics industry, and the belly capacity of aircrafts increasing by 3-4% a year, and the huge blows to revenue that the pandemic brought with it, the air cargo industry is under immense pressure.  It is the need of the hour for companies to consider automation to seize as many new opportunities as they can.

Redesigned automated processes can help them provide better service with higher quality and transparency. Automating booking, for instance, could make the process up to 90% faster. A fully digitized sales and customer-service experience could push direct shipper-carrier bookings up to 15-20%, from the 5% it sees today. 

In Conclusion

While automation is one of the most exciting revolutions set to disrupt the transportation industry, it’s not a change that will be seen overnight. All experts point to a slow but sure change – one that might take years, but will certainly transform the industry into something that is a completely different creature from the one we see today. 

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A hill-state in the north of the Indian subcontinent – famed for its untouched natural beauty, snow-capped mountains, and pristine lakes – has been especially vulnerable to fatalities caused by road accidents. 

Although not wearing seatbelts and drunken driving are among the leading causes for these accidents, a surprisingly high number of them were also caused by bad road conditions like potholes, steep gradients, a lack of crash barriers and roads under construction. Adding to this are the accidents caused by extreme weather conditions – the state has extremely different weather conditions than the rest of the country, with snowstorms and hail being a regular occurrence. 

The government realized that in this era of digitization, a comprehensive digital solution to manage road accidents and safety is one of the primary tools they should consider using to minimize the losses these accidents cause, and began to search for a solution that could effectively capture the complex data that needs to be recorded in the difficult terrain of their state.

Why go digital for road safety?

In most of the countries, stakeholders in the transportation sector currently depend on legacy software platforms and solutions to perform different operations for generating accident and safety reports, analyzing issues, and recommending countermeasure actions. The tools and techniques employed are also holding back their capability to process data from different sources. There are also challenges in terms of rigidity while accepting inputs, user-friendliness, and so on. To overcome these inabilities of the outdated legacy systems, and to approach road safety management scientifically, to arrive at targeted solutions that improve road safety, a digital solution is the need of the hour. 

Enter Experion

Experion, in a project funded by the World Bank, worked with a renowned the British transportation firm to develop an ingenious digital solution that brings all types of data sources, analytics, and dimensions into a single solution framework and makes it easy to perform all analysis and recommendations on a single platform.

The solution is a step towards scientifically addressing road safety management – it helps identify accident-prone spots, reasons for accidents, and measures for taking remedial action in this direction. This solution also helps vital stakeholders such as the Public Works Department, Police Department, Transport Department, and Department of Health and Family Welfare to collaborate effectively and efficiently to ensure road safety.  

The State  Govt zeroed in on this solution to help them battle the number of road accidents they had been facing, and to help minimize the number of lives lost to these avoidable mistakes. They have implemented the solution and have been successfully working with it for over five years now. 

What features does a road safety management system need?

The solution should provide near real-time, complete, and relevant information on road accidents occurring in any part of the country or state to concerned authorities.  

The solution should identify accident-prone locations and analyze trends in road accidents to monitor the roads’ safety. This will enable stakeholders to plan more efficient strategies in line with international safety standards to reduce the number and severity of road accidents and their impact on human lives. 

Advanced geospatial algorithms must be used to identify road safety problems of each specific region and recommend counter-measures to reduce casualties from road accidents. 

How solutions like this one can help 

The solution is equipped with a real-time alert mechanism that enables the concerned stakeholder to reach the accident site and capture various critical parameters of the accident like the GPS coordinates of the accident location, type of vehicle, details of those involved in the crash and pictures. This data can be analyzed and generate meaningful insights such as accident data status, accident severity analysis, reasons, and impacts of the accident, etc. 

As a platform that would be used by different members of the local government bodies, it was built to ensure a superior user experience to all stakeholders, making it easier for them to report even the minor accidents that go unreported due to the complex manual procedures involved previously.

Leveraging the meaningful insights our system provides, the concerned authorities can develop and implement safety performance indicators – measurements that are statistically related to accidents or injuries and are used in addition to accident or injury statistics to indicate safety performance or to understand the process that leads to accidents.  

The digital solution monitors and assesses the road safety situation in each stage of road development and enables stakeholders to make interventions early if they show undesirable results. The solution also allows users to measure and compare safety measures implemented in different countries and compare the before and after scenarios and data after specific actions were taken. 

The solution tracks, stores, and analyses the most salient road safety issues and sorts them according to their contribution to fatalities and injuries. With this, the road authorities can set road safety targets and relevance standards. These targets and standards can be used to educate the road users, the drivers, the vehicle, and the infrastructure manufacturers to improve the road safety situation. 

The solution enables authorities to formulate and develop superior road safety strategies and action plans based on inputs, targets, and safety performance indicators customized for each geographical region. The system also allocates each action plan to the most suitable department for implementation and monitoring. It collects feedback and analyzes its effectiveness and suggests alternatives or tweaks if the accident rates do not reduce.

Conclusion

Our transportation practice is determined to contribute towards safer roads, utilizing advanced digital technologies like artificial intelligence, machine learning, IoT, and advanced analytics. If you have a requirement we can help with, please contact us at sales@blackrockdxb.com.

The post How a Digital Solution by blackrock Helps to Reduce Road Accidents appeared first on Black Rock IT Solutions – Software Product Engineering Services.

Micro-transit offers superior customer experience and improved efficiency of services with real-time supply and demand, dynamic pricing, tracking, cashless payments, customized seat location, and so on. This drives numerous transit agencies to offer micro-transit services in different capacities. Micro-transit transportation could be an alternative to otherwise public transport commuters, and the trend is likely to rise going forward. 

Customer retention is high as long as the providers can ensure a seamless experience, which can be assured by the IT experts that provide software solutions to these companies. Leveraging solutions providers’ technology expertise, micro-transit companies can meet changing market requirements of shared urban mobility sustainably.  

How we developed an on-demand micro-transit product empowered with a scalable, high-performance ride-matching and relay algorithm

Transportation enterprises providing on-demand taxi services constantly look for methods to increase operational efficiency by reducing the time required for a passenger (demand) to get the cab (supply) as well as for the cab drivers (supply) to engage in the next ride request (demand). 

The main component of such an on-demand micro-transit solution is the Ride matching and relay algorithm, which identifies the cab for a specific ride request.

Objectives / Design considerations for the algorithm:

• The application should respond to ride requests in real-time to ensure that passenger spends minimal time on ride searches.
• It should handle the unpredictable peak-request-load for ride requests. The algorithm should auto-scale to handle all the requests and still provide the same performance as regular non-peak hours.
• The algorithm functions based on multiple configurable parameters like geospatial proximity, dry run distance, provision for a uniform opportunity, ride request rejections, average KPI ratings of drivers and passenger, variable pricing strategies, live location of a cab, etc.
• It should be able to integrate with online navigation services which consider congestion data. The algorithm should execute geospatial queries for the real-time calculations involving driver-vehicle location data.
• The algorithm should ensure that service is available 24*7 

Why did we choose AWS Lambda with Python?

The application should be designed to handle a large number of concurrent ride requests during peak times without impacting its performance. With limited time to market, we started exploring cloud-based services that could work as a platform for the algorithm to run. 

AWS Lambda was known to be highly scalable and could process high loads. Lambda has a serverless architecture, which means that you do not have to keep an instance of the server running at all times. The product was being developed in .NET for APIs, and since AWS Lambda supported .NET, it was the natural first choice.

We completed a proof of concept using AWS Lambda with .NET functions. However, during the proof of concept phase, it was found that there was a weakness in Lambda named ‘Cold Start’. We had to find a solution to manage cold starts. 

What is a Cold Start?

Cold Start is the ‘start-up’ time required to get a serverless application’s environment running when it is initiated after a period of inactivity. Lambda applications run on ephemeral containers managed by AWS. AWS has its own complex algorithms to manage the infrastructure dynamically based on what we have subscribed to in the Lambda configuration. If Lambda services are not being invoked for a while, the containers managed by AWS Lambda shall shut down to save its valuable computational and memory resources. When the Lambda service is triggered again, resources must be allocated to it again, which results in latency. 

When we tried the proof of concept with AWS Lambda services written in .NET, we noticed that the cold start time was in the range of 5-10 seconds. Our business APIs were written in .NET. GIS-based APIs were written in Python as it had excellent libraries to handle geospatial functions and data volume. Since AWS Lambda supported Python, we decided to try Lambda services written in Python.

Cold start for AWS Lambda with Python was noticed to be less than half a second, and hence we narrowed down on using AWS Lambda with Python services.

Designing the ride-matching and relay algorithm 

Having settled on the technology to be used, we designed the Ride Matching and Relay Algorithm as follows:

• We decided to use DynamoDB in AWS to store and manage the ride requests. DynamoDB had very good read or write response times and is known for its performance along with the ability to auto-scale. The ride requests from passengers were written into an AWS DynamoDB table. Multiple ride requests may be raised concurrently by different passenger.
• Ride matching and relay algorithm picks up the ride requests from the DynamoDB for processing.
• The algorithm is designed with a three-level hierarchy of Lambdas to separate layers of responsibility to optimize the execution time.  Each layer processes information and returns the result to the parent Lambda function:
  • Level 1 Lambda – This Lambda service sits at the highest level. It reads the DynamoDB table for new ride requests at regular intervals. It groups a set of ride requests and spawns level 2 Lambda services. 
  • Level 2 Lambda – This Lambda service gets a set of ride requests as input. Its main function is to further spawn multiple Level 3 Lambda services for each ride request, accept the selected cab driver for the ride request, and write this into the DynamoDB for a ride request.
  • Level 3 Lambda – This Lambda service gets a specific ride request ID as the input. The objective of this Lambda function is to identify the cabs that qualify for the ride request, score them, and find the highest-ranked cab to serve the ride request. This scoring is based on multiple parameters like distance, time, driver KPIs and many more.

• Based on the cab driver allocated against a ride request, the algorithm will invoke another Lambda service to send the ride request to the driver’s mobile app. 
• In case the driver rejects or misses the ride request, the ride request is passed to the algorithm again.
• If the algorithm is not able to find any supply for the ride request after X seconds another Lambda service will remove all the expired requests.

Achieving the desired output &  delighted customers

The application was developed and deployed into production and met all client expectations and market requirements, which in turn resulted in happy customers. Customers are able to find rides using the application with minimum waiting times, thanks to the ride relay algorithm. The response time of the algorithm was consistent across different loads. There were even scenarios where the peak volume of ride requests went much above the expected levels. No deterioration in performance was noticed and the system was able to cope up with the unanticipated levels of load.  

In conclusion

Our ability to reap the benefits of on-demand micro-transit transit services will depend on companies’ creating superior products that support and meet dynamic market conditions. We at blackrock are proud to have developed and delivered a micro-transit on-demand product with high potential for innovation and scalability, reduced costs, ensuring tangible benefits for our client. 

If you have a challenging idea for the mobility and transport sector and require an IT partner who’s equipped to help you make it happen, please feel free to get in touch with us at sales@blackrockdxb.com  

The post Designing Micro-Transit Ride Matching and Relay Algorithm appeared first on Black Rock IT Solutions – Software Product Engineering Services.