Tag: software development company in UK

It is no secret that India has planned to space flight program and has the idea of sending astronauts to space and the moon.  One of the fundamental challenges this will entail is the safety of human life and how to monitor various health conditions of the astronauts in space and in generally ensuring their well being. This is possible with the concept of remote monitoring and is closely related to the emerging field of Internet of Medical Things (IoMT). As the best software development company in USA and a leading cybersecurity company in UK, GRhombus Technologies analyses this emerging field of IoMT.

IoMT has a primary focus on improving healthcare monitoring, delivery and decision making by integrating medical devices and technologies with the Internet. When various medical devices are connected, it enables easy data collection and sharing across media. Further, there is closer patient monitoring and it is possible to go in for a high level of personalization in treatment.

Some examples of IoMT devices include but are not limited to:

1. Wearables like fitness trackers and health monitors
2. Smart medical implants and automated drug delivery
3. Remote patient monitoring and medical alert systems
4. Assisted living systems
5. Robotic surgery etc.

There are several advantages of IoMT. They are

1. Remote and easy

Gone are the days when a doctor had to be by the patient’s side and undertake rounds. Today, with IoMT, remote monitoring is facilitated. Further, the monitoring is comprehensive with not only the vitals being monitored, but also and advance detection of anomalies and thus helps in proactive and timely intervention.

2. Personalized and improved healthcare delivery

With the various parameters being monitored continuously, there is personalized treatment regimen. Further data can be shared across platforms and healthcare providers easily. Long-term effects and trends based on lifestyle and other factors can also be studied. All this leads to better outcomes for patients, care givers and healthcare professionals.

When treatment is highly personalized, then the medical intervention is more targeted and the success of the outcome is also assured.

3. Research and development

With the availability of ready data, research is facilitated. Right from large size sampling to understanding disease trends across various geographies and age groups, medical research can play a key role in understanding conditions better and even with formulating policies.

4. Collaborative effort

With IoMT, patients and their families and caregivers are more in control as the data is transparent and measurable. This helps healthcare professionals better communicate and collaborate with the patients. Patients can also monitor progress and draw psychological comfort. By being more participative and collaborating to make informed decisions, the overall scope of medical effectiveness and patient empowerment is increased.

5. Cost considerations

With timely intervention, costly medical complications can be avoided as the case is handled before an escalation. Further, resource allocation for patient monitoring is optimized. Patients also need not travel to the hospital from their location. This all adds up to cost effectiveness for all parties.

Overall, IoMT is an emerging field and has excellent scope. While concerns remain around areas like data collection, security, data volume etc., the long-term positive impact and considerations are sure to win when reasonable safeguards are put in place.

Why Grhombus Technologies?

Grhombus Technologies is a leading software testing company in UK and has the best IoT testing experts on its rolls. We bring a layered approach to any IoT solution. Our segment-wise approach ensures that we bring 100% coverage to all IoT systems, right from the hardware and network to the data storage, cloud and final application.

This comprehensive approach has helped us win the admiration of clients and we have emerged to be a leading software development company in UK. Apart from IoT, we also have expertise in a range of services and areas including Devops, Salesforce, EdTech and Cyber security.

Since time immemorial, humans have used language and speech as a medium of communication of thoughts. As computers evolved, they had their own programming languages and codes. Software became advanced over time and coupled with hardware advancements, the potential for computer applications became endless.

The next step in this evolution is the case of Natural Language Processing or NLP for short. It is a field of artificial intelligence (AI), whose aim is to help computers understand and interpret human languages. The understanding and interpretation by computers must be in a way that is useful, and it is possible by advanced models, algorithms and other related developments.

The main applications of NLP include areas like

1. Machine-based translation
2. Summarization of information
3. Generation of text and language in a coherent manner based on various data sources. For example, writing about the performance of a company based on a summary of the balance sheet and other related financial data.
4. Chatbots and conversational agents

And many more such applications.

As the best software development company in USA and a leading cyber security company in UK, GRhombus Technologies analyses the recent trends in NLP in the below blog.

1. Ethics

As AI gains traction, one of the key areas to address is how NLP models can be trained to avoid bias and remain ethical. There is also an inherent fear of systems acting recklessly to take decisions. This is especially true in the case of customer-facing applications like chat bots.

2. Privacy concerns

Along with ethics, privacy concerns associated with NLP also need to be addressed. This is still a grey area and there are discussions at multiple levels on how various aspects need to be handled.

3. Quick-learning models

Humans have the inherent ability to learn new things even when the data around the project is limited. The aim is to extend this to NLP with few shot and zero shot learning. This also applies to cases where the data set is limited like in low resource languages.

4. Transparency and accountability

As NLP finds a larger scope of applications, it is important for end users to understand how decisions are made. Insights need to be provided on how the model behaves and what its limitations are.

5. Transfer Learning

There are many cases where learning in one task can be applied to a related task. More research is being undertaken in this area to quicken the evolution of NLP.

6. Multilingual capabilities

Language limitations themselves become a barrier sometimes. For example, a person may understand and speak Chinese, but not Spanish. The context also varies between different languages. So, the aim with multilingual capabilities is to bridge the divide and provide better communication and understanding across different languages.

Overall, the focus is on improving the ethical aspects around NLP as well as expanding the application across different verticals.

About GRhombus Technologies

As a leading software development company in USA and a reputed Salesforce CRM customisation company, we understand the tenets of a business and tailor the solution to a required business need. We are also well-versed in the Force.com development platform and can undertake key customisation and advanced automation functions based on the business needs.

We are also one of the leading custom app development company in UK and we offer a one stop solution for developing Web, Mobile and Cloud based applications with a responsive design that suits specific business needs. Are you interested in engaging with us and growing your business to the next level? Contact us to fly on wings of change.

It is no doubt that artificial intelligence (AI) and machine learning (ML) have revolutionized different aspects of various industries and business verticals. They have helped create new business models, add efficiency into the system and even understand customer perceptions and interactions better.

One area where AI, ML and Robotic Process Automation (ROPA) can find good applications is in the field of software testing. Oftentimes, one or more such tools can be combined to achieve stellar results. This is where the concept of hyperautomation testing comes in.

In layman terms, hyperautomation testing refers to the use of advanced technologies, such as artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA), to automate and streamline the testing process. The key feature of hyperautomation testing is how it is able to analyze large volumes of data by leveraging various AI and ML algorithms to identify patterns, make intelligent decisions and improve the testing process. It can also be used to validate system behavior, automate the generation of test data, reduce manual effort and perform continuous testing.

As the best software development company in the USA and a leading software development company in UK, GRhombus Technologies has done key work in this area. In our experience, some of the key advantages of hyperautomation testing are:

1. Reduced time to market

Using hyperautomation testing, many manual and repetitive tasks can be automated and this will help in faster time to market of the product. Automated tests can run 24/7 and catch issues early and human resources can focus on other important areas.

2. Increased quality

With automation, the depth of testing and the breadth of testing can be increased. This includes areas like more use cases, browsers, devises etc, which may not be possible in a manual testing setup. This will ensure that quality is built into the testing process.

3. Consistency

Since there is no fatigue involved like the case of manual testing, hyperautomation eliminates human errors and inconsistencies. Since the breadth and depth of testing is more, it also means that errors can be caught early. The feedback loop is faster and more robust.

4. Ability to scale

With an automated test setup, it is easy to scale without any corresponding loss in quality. The same may not be possible in a purely manual setup.

While we discuss the advantages, it is also important to have a balanced perspective of things. Some of the key disadvantages of hyperautomatino testing are listed below.

5. Investment in time, infrastructure and capital for setup

From the perspective of hyperautomation testing, developing automated test scripts and building out the necessary infrastructure requires significant initial investment in tools and knowhow. Hence, it is necessary to weigh the pros and cons before making a final decision to go in for a hyperautomation setup in the organization.

6. Maintenance

As with all tools, even a hyperautomation testing setup needs maintenance. They have to be updated as the test cases, applications and envionments evolve. Further, when defining automated test scripts, they should be free from bugs. Else, they can lead to false positives/negatives in results. Further, a certain amount of foresight is required as automated tests must me capable of meeting future needs and should not be brittle.

7. Skill

Writing automated test scripts requires skill and deep coding expertise. Further, the modules must be clearly defined and designed and when error messages are thrown, it should be easy to identify the root cause.

Why GRhombus Technologies?

GRhombus Technologies is a leader in offering cyber security solutions and software testing solutions. We are a trusted information security partner for leading companies in Europe and USA.

Apart from cybersecurity and software testing, we are also a leading software development company in UK. Established in 2014, GRhombus Technologies has delivery centres in India at Hyderabad, Chennai and Bengaluru, and partner offices located in the USA and the Netherlands.

For additional details, please contact us.

Artificial Intelligence (AI) is the process where computer systems can perform tasks that typically humans perform including research, decision making etc. The computer systems can also be trained to solve problems and all of the above occurs by training the computer systems in studying data and patterns in the same.

AI is a broad umbrella and under it, there are different categories like robotics and related applications, machine learning, natural language processing etc. As a leading software testing company in UK and software development company in USA, GRhombustech brings rich expertise to the field. Based on our experience and observations, some of the ways AI can help achieve better results in software testing are

1. Automation of processes

Test cases can be automated by self-learning machine algorithms. Further, with more machine learning, test scenarios themselves can be identified and the system can also come up with proactive suggestions. Certain repetitive and time consuming test tasks can be readily automated and such tests can provide a wealth of information on software and code stability.

2. Focus Areas

With the analysis of historical data by AI systems, critical focus areas can be easily identified. This will help to proactively fill the gaps and undertake better testing. Thus, the weakest link in the chain will be identified easily and covered, thereby ensuring a stable release. Test cases can also be grouped based on impact and relevance. Thus, the number of test cases can be optimized without any compromise on the integrity of the testing process.

3. Analysis of test logs and associated data

AI can analyze the test logs to identify patterns and anomalies that may not be noticed during a manual analysis. This is especially true in the case of complex software products where the links may not be directly evident. This helps in identifying and resolving issues more quickly.

4. Security perspective

AI can also make specific analysis of code and test software from a security and vulnerability perspective. As the best cybersecurity company in UAE, GRhombus has a variety of tools and techniques in the domain of cyber security.

5. Simulations

AI can simulate user behavior to test the software under different scenarios. By using techniques like reinforcement learning, this will help identify trends and bring a more real-world use case to the testing perspective in the test bench itself!

6. Quality

AI can integrate in a CI/CD (Continuous integration/Continuous Delivery) pipeline. This allows software testing throughout the process and thus ensures quality throughout the process. Defects reaching the live/production scenario are thus minimized.

The main advantages of using AI for testing are:

1. Less errors due to human fatigue
2. Scalable solution
3. Ability to handle different complexity levels of testing simultaneously
4. Enlarged scope and coverage of testing
5. Faster testing and result delivery without compromise on the integrity of testing
6. Precise testing in identified areas
7. Predictive analytics can be incorporated

About GRhombustech

GRhombustech is a leading software development company in UK. Apart from software development, we are also among the leading cyber security companies in UAE. GRhombus has established itself as a pioneer in Data Visualization, Edtech, IoT Testing, Salesforce Development and Cloud Testing. Driven by the guidance of experts with more than 25 years of industry experience, the GRhombus family now has over 200 employees. Established in 2014, GRhombustech has delivery centres in India at Hyderabad, Chennai and Bengaluru, and partner offices located in the USA and the Netherlands.

For additional details, please contact us.

Often, applications require coding expertise for development. Now is it possible to create applications without any knowledge of coding? Yes. It is possible and that is where the concept of low-code or no-code automation comes in.

When an application can be developed just by drag and drop options and through GUI (graphical user interfaces) and configurations, then it is no-code automation. Thus, businesses or even lay users can create applications without any (or even if necessary, very minimal) coding knowledge.

As a leading software development company in USA and a leading cybersecurity firm in UK, we bring robust solutions. The below is our analysis on the concept of low-code/no-code automation.

Advantages of No-Code Automation

1. Plug and play and speed of development

Since there is only drag and drop options and a user interface, low-code/no-code platforms significantly reduce the time it takes to develop and deploy applications. Use of pre-defined templates also reduces the need for any coding.

2. Cost Savings

Since less-technical expertise is required, there is no need to hire developers or software professionals. If the low-code application completely satisfies the business requirements, then faster time to market is achieved. This also gives profits and cost savings.

Further, with no-code applications, scalability is also easy. This means that when the initial pilot project works successfully, it can be enhanced easily to other areas.

3. Larger user base

By ensuring that no coding is involved, non-technical users can develop solutions. This leads to a larger user base and enhanced footprint of technological and software applications. This can drive digitization, and digital adoption in new sectors.

While there are the above advantages, the disadvantages are

Disadvantages of Low-Code/No-Code Automation:

1. Limited possibilities

When a ready-made solution is used, the customization possibilities are limited. Thus, any specific business challenge will require either a custom-built application or a work-around. Often, work-arounds do not fully satisfy the requirements and only cause frustration for users.

2. Dependency and security

When low-code solutions are used, there is dependency on a single vendor or a company. Such kind of dependency can be unhealthy for business continuity as the organization scales up. Further, data security, application security and other parameters may be difficult to ensure. This can make organizations vulnerable to attacks.

3. Performance Issues and hidden costs

Applications built with low-code/no-code platforms may not perform as well as those built with traditional coding, particularly for complex or large-scale applications. Further, hidden costs like license fees or anything else can also apply.

Some of the ways in which no-code or low-code applications work are:

1. Visual Workflows

By simple drag and drop, an entire workflow can be defined. An example is data entry. In this case, the entire application can be opened and the data that is obtained from a source entered automatically.

2. Integration platforms

These provide pre-built integrations or connectors to various apps and services. An example of this is automatically adding new email subscribers to a CRM.

3. RPA (robotic process automation)

This uses “software robots” to mimic human actions like mouse clicks, keyboard inputs, etc. Useful for automating repetitive computer-based tasks.

About GRhombus Technologies

GRhombus Technologies is a leading software development company in UAE and the best software development company in UK. The company has made a mark in various spheres like end-to-end Software Development, DevOps, Manual Testing, Automation Testing, and Security Testing. We are also a recognized leader in the domain of cybersecurity solutions. GRhombus Technologies is dedicated to world-class customer service, innovations and cutting-edge solutions. For more details, contact us.

Today mobile devices have become ubiquitous. So much so that we cannot imagine life without them. Right from controlling our doors and heating to communication, mobile devices have changed the way we view the world. Fundamental to all this is wireless technology.

6G is the latest wireless communication technology which is still in the research and development phase.

Some of the main advantages of 6G or sixth generation wireless technology are:

1. They offer higher speeds and less latency than what is presently available.
2. They can incorporate AI based controls. This will mean highly efficient network selection, data processing, network management and decision making.
3. Connectivity will be seamless and reliable, even in highly crowded environments or even remote areas.
4. Global coverage can be achieved with 3D networking possibilities. Thus, ground, ariel and satellite networks can be used effectively.

An extremely important point that sets 6G apart will be the environmental sustainability and positive environmental impact. The hardware is envisioned to be more energy efficient and will thus consume less power. Similarly, renewable energy sources can be integrated to make base stations self-powered. Power consumption can be adjusted dynamically based on the load and other conditions in real time. Spectral efficiency will be achieved by using tetrahertz frequencies and spectrum can be reused. Increased virtualization will help save on cost of materials and also the setup of physical infrastructure.

While many parts of the world are seeing 5G rollout and implementation, it is interesting to see the advantages that 6G will have over 5G. Though 5G and 6G are both wireless communication technologies, the key differences are as follows. This analysis is based on our experience as the best software development company in UK and a leading software development company in USA.

1. Speed

5G networks offer speeds up to 10 Gbps, while 6G is expected to provide speeds up to 100 Gbps. Thus, there is a direct 10 times faster speed advantage.

2. Capacity

Due to increased speed, more devices can be supported.

3. Latency

5G has a latency of around 1 millisecond, while 6G is expected to have a latency of less than 1 millisecond.

4. Wider application net

Due to low latency, mission critical applications can be easily onboarded in 6G. This includes applications like autonomous driving, holographic communication, highly immersive applications like augmented reality and virtual reality. Connectivity will be applicable across a lot of different systems than is available at present with 5G. This will also help to create personalized experiences.

5. Frequency Bands

5G operates in frequency bands up to 100 GHz. 6G, on the other hand, is expected to operate in the terahertz frequency bands (100 GHz to 10 THz). Thus, there will be greater bandwidth available for use.

Why Grhombustech?

Grhombustech is a leading software testing company in UK and has the best iot testing experts on its rolls. We bring a layered approach to any IoT solution. Our segment-wise approach ensures that we bring 100% coverage to all IoT systems, right from the hardware and network to the data storage, cloud and final application. This comprehensive approach has helped us win the admiration of clients and we have emerged to be a leading software development company in UAE. Apart from IoT, we also have expertise in a range of services and areas including Devops, Salesforce, EdTech and Cyber security.

AI as a Service (AIaaS) refers to the provision of artificial intelligence (AI) tools, technologies, and algorithms as a cloud-based service over the internet. Some of the most popular service providers include AWS web services, Microsoft Azure machine Learning, tools from IBM and Google’s cloud platforms.

What is usually offered is a suite of machine learning (ML) algorithms, natural language processing (NLP) tools, computer vision, and other AI technologies that developers and businesses can access via APIs (Application Programming Interfaces) or software development kits (SDKs).

Some of the key activities that can be achieved through this include image and speech recognition, language translation, and predictive analytics. The output from these services can then be integrated into various applications and services.

AI as a Service (AIaaS) is a model in which businesses can access and use artificial intelligence tools and services through a third-party provider. AIaaS allows businesses to take advantage of the benefits of AI without having to invest in the infrastructure, expertise, and resources required to build and maintain an in-house AI system. Thus, even a small or a medium business can use powerful tools to improve the efficiency, without investing heavily in AI or employing key resources with knowledge in AI.

The steps usually involves a strong business case and analysis on what needs to be achieved. Without this clarity about the problem, a solution cannot be arrived at. Similarly, only if the problem statement is clear, will the tool and data set that is required to be used be understood.

The next step involves choosing a good AIaaS provider who offers the service suite they need. The business will then hold extensive consultations and finalize the deal. The AI service provider will undertake a consultative approach in helping to refine the problem and arriving at a solution. The business will then prepare and provide the data to the AIaaS provider. The data will have to be in an agreed structure and format and this can then be used to train the AI model.

The AIaaS provider can also work with the business to integrate the AI models into their systems and processes. This can include integrating with existing software, creating new interfaces, and providing training and support to users.

Continuous testing and optimization is necessary to achieve success. Once implemented, the business can quickly see the benefits and use AI to automate processes, gain insights, and make data-driven decisions. Giving feedback and training the system is the key to success.

Overall, AIaaS allows businesses to access and use AI capabilities without the cost and complexity of building and maintaining their own AI infrastructure. It provides a flexible and scalable solution that can be tailored to meet the specific needs of each business, while also providing ongoing support and optimization. By making an informed decision and by engaging with the right partner, a business can scale unmatched heights and exceed customer expectations.

About GRhombustech

GRhombustech is a leader in offering cyber security solutions in UAE and is a trusted information security partner for leading companies in Europe and USA. We take pride in customising security programs per customer needs and offering flexible and elegant solutions. Our experts deliver detailed analysis and documentation along with comprehensive mitigation and testing solutions at every step.

Apart from cybersecurity, we are also a leading software development company in UK and can implement Salesforce solutions in USA. Established in 2014, GRhombustech has delivery centres in India at Hyderabad, Chennai and Bengaluru, and partner offices located in the USA and the Netherlands.

For additional details, please contact us.

Software and programming have revolutionised the way we work and have positively impacted human life at every level. Today, there is no field in the world that is immune to the software revolution.

Traditionally, software development proceeded on a monolithic architecture. In such a case, the entire system is developed as a single unified system. The codebase contained all the necessary components, such as the user interface, business logic, and data storage. Thus, all components shared the same memory space, and the entire application was running as a single process. This approach was easy to code and deploy especially for small scale software projects. However, as software projects became more complex and mission critical, such a monolithic approach had its inherent limitations. It was difficult to maintain the software and install patches and upgrades. Further, with increasing IT penetration and expanding user base, scaling up of systems was also a challenge.

Testing was difficult and making changes to one part of a system could have an impact on some other part. It was also difficult to trouble shoot in such cases, with testing also becoming cumbersome.

Considering the above limitations, many organizations moved away from a monolithic architecture to a more user and deployment friendly architecture like microservices or service-oriented architectures.

A microservice architecture is a type of software architecture wherein an application is composed of small, independent, and modular services. Each microservice performs a specific function and communicates with other microservices through well-defined APIs or any other light-weight protocol.

Some of the advantages of microservices are:

1. Robustness and Scalability

Microservices are usually small and self-contained. Hence, they can be scaled up or down as needed. This means that the application can handle varying levels of traffic and workload without impacting performance. Even if one part of the application fails, it does not bring the whole roof down (literally!).

2. Agility in application

Each microservice can be developed, deployed, and maintained independently, which allows for greater agility in the development process. Teams can work on different parts of the application without having to worry about breaking other parts, unlike in a monolithic architecture where all parts are held together as one unit.

3. Diversity in application of technology

Different services can be developed using programming languages, frameworks or technologies, depending on the specific requirements of each service. Thus, the best can be chosen for a specific function and this will deliver amazing results in overall performance.

Some very famous use cases of microservices being actively used are:

1. Amazon

Amazon actively uses microservices for application development and deployment.

2. Netflix

Netflix has over 500 microservices that run and is a great example of smooth performance even in conditions of high load or varying traffic volume.

3. Airbnb

Considering the business case of Airbnb, it is vital that users be notified on different devises and have a seamless experience right from logging in to making a booking. In such cases multiple channels and platforms being used, microservices are the best bet to success.

4. Best Buy

Best Buy was an early pioneer and started migrating to a microservices framework to manage and transform their e-commerce portal.

Overall, microservices offer a more decentralized approach, where each service can be updated and improved without disrupting the entire system. They are cheaper to develop and deploy and considering increasing complexity of software projects, microservices look to be among the safest and best methods forward.

About GRhombus Technologies

GRhombus Technologies is a leading software development company in UK. Apart from software development, we are also among the leading cyber security companies in UAE. GRhombus Technologies has established itself as a pioneer in Data Visualization, Edtech, IoT Testing, Salesforce Development and Cloud Testing. Driven by the guidance of experts with more than 25 years of industry experience, the GRhombus Technologies family now has over 200 employees.

For additional details, please contact us.

Datafication refers to the process of turning various aspects of everyday lives of people like their behaviour, transactions made, social interactions etc into data in a structured format. This data can then be analysed using various data-analysis techniques and advanced technologies to glean information.

Technologies and developments in the arena of big data, machine learning, artificial intelligence etc have led to the increasing popularity of datafication.

Understanding Datafication with an Example

GRhombus Technologies, the best custom software development UK has to offer and among the leading cyber security companies in UK has deep experience in this domain. To understand the concept of datafication easily, let us understand the same with an example.

Consider a common health/fitness tracker or a health watch. They commonly collect data like heartbeat and pulse rate, number of steps walked, sleep patterns etc. This raw data is then stored and analysed by the system and displayed in a mobile or desktop application. The user can then get insights into their health and get personalized recommendations based on available scientific facts to help enhance their lifestyle and improve well-being.

Now consider that this data collected from various individuals is pooled. This polling and aggregation will give a larger data set. By analysing this data set, one can get insight on the general health and well-bring of a population. This can in turn help set up public health policies, investigate scientific approaches to improve health, provide specialized healthcare etc. Thus, society can benefit as a whole by this process if used correctly.

Today, datafication has led to the development of new business models, services, and products that leverage data to generate insights, create value, and drive innovation.

Some of the advantages of datafication are:

1. Robust decision-making

Datafication can help organizations make better decisions because they have access to more accurate and up-to-date information. By analyzing data, companies can identify patterns and trends that would be difficult or impossible to identify otherwise. This is especially true in sales trends, personnel productivity etc.

2. Improvement in efficiency

With a study of the data available from datafication, one can automate processes and reduce the time and effort required for tasks such as data entry, analysis, and reporting. This can lead to significant cost savings and increased productivity.

3. Achieve customer delight

By collecting and analyzing customer data with the active permissions of customers, organizations can gain insights into customer behaviour and preferences. Thus, companies can offer custom solutions and delight customers with their offerings.

4. Innovation

By analysing the data, organizations can identify trouble spots and innovate to achieve value both for the organization and for customers.

5. Manage and mitigate risk

By analyzing data, organizations can identify potential risks and take proactive measures to mitigate them, reducing the likelihood of costly incidents. This is especially true in the financial domain where analysis of data can help prevent fraud.

GRhombus Technologies

GRhombus Technologies is a leading software development company in USA and has the best cyber security experts in the business. From smart devices to technology stacks, we have end-to-end capabilities in the IoT domain and Salesforce implementation.

We are led by a dedicated and experienced team and take pride in offering cutting edge solutions to any business challenge. We have helped many businesses unlock potential and deliver value.

For any additional queries or business needs, feel free to contact us!

Driverless cars (also known as autonomous cars or self-driving cars are the latest innovations in technology. Right from Uber to Google, a lot of companies including automotive companies are investing in this technology to make driving easy. It uses a combination of sensors, cameras, radar, and artificial intelligence (AI) to sense its environment, analyze data, and make decisions about driving actions.

The aim is to completely replicate the actions and decision making of a good driver and also allow for a human override function, which allows a person to take control of the vehicle in certain situations. However, though ambitious, this technology is difficult to master.

Why is Autonomous Driving Difficult to Achieve?

Decision-making complexity

It is well known that even simple actions human actions are difficult to replicate. Autonomous driving involves decision making based on complex data sets with inputs from multiple sources, including real-time sensor data, road maps, weather conditions and traffic patterns.

Timing

While decision making is complex, it should also be done within a short time to ensure safety of passengers, other road users etc. Sometimes, split second decisions may be involved.

Unpredictability

On-road scenarios and conditions can be unpredictable and change rapidly. From a pothole to crossing pedestrians, changing weather, sudden rains etc, the list of unpredictable scenarios that can arise is countless.

Safety Concerns

Passenger safety must never be compromised. Any hazards must be immediately identified, and action taken. This is also the case when the driver may doze off.

What is the role of AI in Autonomous Driving?

AI plays a critical role in autonomous driving. Right from sensing the external environment to data gathering analysis and decision making, everything must happen seamlessly. Self-driving cars rely on a variety of AI technologies, including machine learning, computer vision, and natural language processing, to operate safely and efficiently. They are explained in detail below:

Machine Learning

Machine learning algorithms are used to train self-driving cars to recognize and respond to different objects and situations on the road. An autonomous car must be able to differentiate between pedestrians, animals, objects, other vehicles etc. As self-driving cars collect more data and learn from their experiences, their algorithms become more accurate and effective.

Based on this data that is gathered, decision making must be done. Path planning and determination of the most safe and efficient route is also undertaken by machine learning. Autonomous vehicles require high-precision maps to navigate the roads. Machine learning algorithms can analyze sensor data and create detailed maps of the environment.

Another important parameter is determining the behaviour of the driver, detecting signs of fatigue and distraction and taking appropriate action.  A driver must always be alert and ready to take control of the vehicle if necessary.

Computer Vision

Computer vision allows autonomous vehicles to “see” the world around them using cameras, sensors, and other devices. Computer vision algorithms are used to interpret visual data from these devices and identify objects, people, and other relevant information in the environment.

It is used for detecting objects, lanes, traffic signals, obstacles, pedestrians etc and then decisions are made accordingly.

NLP

Natural language processing (NLP) is used to enable self-driving cars to communicate with passengers and other drivers. NLP algorithms allow self-driving cars to understand spoken or written commands and respond appropriately, for example, by adjusting the temperature or navigation route.

NLP involves speech recognition to understand verbal instructions and commands, understanding the emotions and intent, answering queries, text-to-speech conversion etc. It should also bring high levels of contextual awareness and gradually understand the driver/user’s behaviour to offer a custom solution.

Overall, autonomous driving is a very promising field and it is definite that with more advancements and research, 100% autonomous driving will be achieved in the future.

About GRhombustech

Grhombustech is a leading software development company in UK and has made a mark in various spheres like end-to-end Software Development, DevOps, Manual Testing, Automation Testing, and Security Testing. We are also a recognized leader in the domain of cybersecurity solutions. Grhombustech is dedicated to world-class customer service, innovations and cutting-edge solutions. For more details, contact us.