10 Best Project Management Tools For Software Development in 2022

Project Management Tools that help software developers to develop applications are called software tools. Today we will have a look at the 5 most popular software tools which are used to develop miscellaneous software. EES is taking a step forward to reconceptualize the methods applications are built. We feel pride in being called a reputed mobile app development company in Dallas that happens to work on the web, VR, GIS, and location-based app development, as well.

Best Project Management Tools

1. Jira

Jira is an issue tracking tool that is used by teams working on a project using agile methodology. It helps a team to plan, track and release software. Jira can be customized and its prevailing features can be used in all phases of development.

2. Zend Studio

Zend Studio is an IDE used for coding and testing web and mobile applications. It is an ultra-fast performance tool that helps in searching, indexing, and validating PHP applications. It helps in deploying PHP apps on all servers even on cloud-like Azure and AWS.

3. Nifty

Nifty is an easy-to-use project management solution that enables teams to create milestones, manage tasks, and files all in one central location. Nifty also has a portable team chat that makes it a breeze for teams to stay in sync.

4. Bitbucket

Bitbucket  Is a source code repository for software project development source code? It is also a version control system based on the web which is used by teams to collaborate on code and also for code review. Its flexible deployment models of Bitbucket make this a very useful tool added by private repositories and collaboration of code on steroids. Etc.

5. GitHub

GitHub is a platform used for development and collaboration for reviewing code and management of software projects. It is used to build software applications and to manage, host, and review code. With help of GitHub, developers have the ability to document the code and then host it from GitHub repositories.

6. Dreamweaver

Dreamweaver Is a powerful tool from adobe that can be used as a programming editor to create all kinds of websites? It has support for different markup languages including XML, JavaScript, CSS, HTML, etc. It is available for windows as well for Linux. The latest version of dream viewer has the option to preview your website even before launching it. You can design responsive websites using dream viewer.

7. Azure

Azure is Microsoft’s cloud computing service to design, deploy, manage and test web-based software and hybrid cloud applications. Services provided by MS Azure include CDN, Virtual Network, Migrate apps, messaging, storage data management, etc.

8. NetBeans

NetBeans is free and open-source software written in Java which is used to build mobile and web applications easily. It is a cross-platform tool that works on all OS like Mac, Linux, Windows, and Solaris. It is full of features like smart code editing, process management, and the development of a user interface.

9. Bootstrap

Bootstrap Is a free and open-source framework for developing fast and responsive mobile and web applications using technologies like HTML, JavaScript, and CSS. It can be customized according to the need of the project because it is open source. It also supports a smart drag and drop facility and supports a wide range of features like pre-built components, plug-ins, sass variables, and mixings that allows its users to make powerful applications.

10. Eclipse

Eclipse is a popular Java IDE that is used for application development by software developers in computer programming. In addition to java, it is also used for other languages like C++, C#, C, ABAP, PHP, etc.

Feather Magazine Theme Vs Image Gridly Theme- A Comprehensive Comparison

Feather Magazine

 Feather Magazine is a multipurpose most ideal WordPress theme for the magazine and affiliate, personal blog, or classic website. It has a more effective and clean and user-friendly design for your websites. This theme offers some boundless limited customization. It is the perfect combination of professional and beautiful blogs.

The theme has a lot of space for advertisement where you can place ads by utilizing the header, sidebar for video advertisement and the image advertisement, etc. It is made for various search engines like google, bing, yahoo so you can easily beat another blogger in the Google with help of our fast Seo Optimized theme. Even you are a beginner you can easily set up the themes without any technical knowledge.

If You are thinking about starting blogging for travel, technology, fashion (such as leather apparel fashion brand, Leatherial), or in any other niches then feather magazine is the responsive and flexible theme.

Image Gridly

 Image Gridly is one of the fully SEO optimized and responsive WordPress themes so it works on different devices like tablets, desktop, mobile phones, that is used for photography, portfolio, blogging, newspapers or stock of image websites.

This theme is so simple to set up and it has a lot of features for affiliate marketing and for advertisement it comes with lots of space. When we are talking about the code, its code is clean for your website to load fast and quick response.

It is a well SEO structured, creative, and modern multi-purpose theme, this theme comes with beaver Pagebuilder, so it allows us to create a corporate converting landing page. It requires less customization to create an attractive design.

Features of Feather Magazine and Image Gridly

Feather Magazine

Image Gridly


Hide Title/ Tag Line

Premium Support

Responsive Design

0.2 Seconds load Tim

Custom Site/Tage Ling

Custom Copyright text

Recent Post Widgets

Right and left sidebar

Easy Google Fonts

Post Formats

Page Speed Plugin

Hide and Show Breadcrumbs

Show Header Everywhere

Hide and show tag section

Customize blog Feed Color

Custom Primary color

Elementor Compatible

Single Post & Page colors

Access All child theme

Custom Navigation colors

Multiple website support

Hide and Show Author box

Hide Logo Text

Gutenberg Editor

Custom Navigation Logo

Space for advertisement

Background Color

Pro and Cons of Feather Magazine and Image Gridly

Pro of Feather Magazine and Image Gridly

Feather Magazine

Feather Magazine is WordPress responsive and SEO optimized and easy to install and customize. You can this theme for multipurpose and as per demand create various professional websites.

Image Gridly

This theme is fully flexible responsive and it is used for especially photography websites and Image gridly is implemented beaver Page builder, it provides some features to create some different purpose of a website and also landing pages.

Cons Of Feather Magazine and Image Gridly

Feather Magazine

The Feather magazine themes are the difficult theme as it is not compatible with One-click for demo import, if you have full content for the news and magazines, then it not comes with Gutenberg editor.

Image Gridly

The Image Gridly has some limited customization features, it provides some fewer customization features for your blog post.

Price Comparison



Feather Magazine

Image Gridly




Business Subscription



Lifetime Access




In this article in short, if you are want to start simple magazine websites and photography websites. Don’t miss these two demanding WordPress themes suitable for your business. EES is undoubtedly a market-proven mobile app development company in Dallas with a well-trained & skilled software development team that meets your app specifications to help you move inside the modern world.

Both themes have good speed and enough features for their various function, So if looking to start blogging, then I suggest you go with Feather magazines.

Electric Vehicle Battery Technology Types And Their Cost

With the old and the new, it is time to go forward. Electric vehicles (EVs) are on the rise and so are electric vehicle battery technology after a recent government decision that the sale of all new fuel and diesel automobiles would be prohibited by 2030. Since Henry Ford’s Model A was introduced in 1903, this is the most significant event to vehicles. Better for the environment.

Are you:

  • Your electric car is charging in your driveway.
  • When is the appropriate moment to make the switch?
  • Electric vehicles: still a bit of a mystery to you?

In any case, it is worth understanding how EVs function because they will play a significant role in the future of transportation. In addition to saving your money, EVs offer a smoother and more enjoyable driving experience than previous generations of automobiles. In terms of batteries and charging, far too many of us do not truly understand how electric cars function.

This means thinking about how far you can drive before you need to charge. We hope that this information may allay your worries regarding the power of the motor. In no time, you will become an expert.

In any case, it is worth understanding how EVs function because they will play a significant role in the future of transportation. In addition to saving your money, EVs offer a smoother and more enjoyable driving experience than previous generations of automobiles. In terms of batteries and charging, far too many of us do not truly understand how electric cars function.

This means thinking about how far you can drive before you need to charge. We hope that this information may allay your worries regarding the power of the motor. In no time, you will become an expert. Unlike old-fashioned batteries, it does not fit neatly under the hood of a car. Instead, it is tucked down under your feet in the bottom chassis, hidden from view.

The battery is very well secured in this compartment. Whatever the British weather may bring, it is designed to function at precisely the perfect temperature. Charging and discharging cycles govern the battery’s operation. All those cells are charged when the car is plugged in, but the power is discharged on the road.

What Kinds of Batteries do Electric Cars Use? 

Here is the nerdy tech part of the article. It will be jargon-free:

Lithium-ion Batteries

  • Lithium-ion (Li-ion) batteries are used in electric cars. Like the ones on your cell phone, they are considerably bigger and stronger.
  • No lithium metal in the batteries, just ions are used in the production of the batteries.
  • Anodes and cathodes are separated by electrolytes, which carry the ions from one electrode to the other.
  • In a nutshell, this movement (approximately) generates electricity.
  • High energy density makes Li-ion batteries ideal for acceleration.
  • You may charge and discharge them hundreds of times without deterioration.
  • In contrast to other types of batteries, EV batteries have a low self-discharge rate.
  • It is time for a chemistry class to end. Batteries for electric vehicles are still in their infancy. In the future, battery technology will improve, resulting in cheaper, smaller, lighter, and more lasting batteries.

How can Regenerative Braking help?

In essence, braking is an inefficient process. It causes a loss of energy and momentum, which slows down an automobile. In other words, an automobile needs to consume more energy to regain its previous speed. Braking is, of course, a vital element of driving. We recommend that you continue to do this.

With an electric automobile, all of the motion energy is wasted when the brakes are applied. On the other hand, electric vehicles use a motor to convert much of the kinetic energy and store it in a battery, ready for use when the car accelerates again. This is a great idea! Batteries gain the energy that would otherwise be lost during braking.

Electric Vehicle Battery Capacity Explained

An electric vehicle features a motor instead of an engine. As with the petrol tank, an electric vehicle is powered by an electric motor. The battery capacity of an electric vehicle is measured in kilowatt-hours (kWh). As an example, consider the following:

  • In other words, the Model S can drive over 400 miles on a charge.
  • For example, the 50kWh battery in an EV (such as the Corsa-e from Vauxhall) is suitable for 209 miles.
  • It may have a 35kWh battery, but it can still go 130 miles on a single charge.
  • As a general rule, the larger the kWhs, the further a car can go on a single charge. Remember, you cannot ever entirely charge or drain an EV’s battery. An ingenious way to preserve the battery, keep it functioning smoothly, and extend its life.
  • Financially, it makes sense to choose an EV with a suitable battery capacity. Buying a Jaguar i-Pace with a 292-mile range is pointless if you will use it around town. When driving long distances, acquire a car with a larger battery, or accept that you will need to top it up more regularly if you do not.

How Long do Electric Car Batteries Last? 

Batteries for electric vehicles include hundreds of cells that allow them to keep their charge after driving hundreds of thousands of kilometers. Most EV batteries now have a life expectancy of up to 20 years3 – which may even outlast the vehicle itself!

It is a good thing to know. As the technology continues to advance, so too will the battery life of electric vehicles.

How much does it Cost to Replace an EV Battery? 

In the lifespan of your automobile, you are unlikely to need to replace your car’s batteries. Be sure to verify your warranty and make sure it protects you if a battery failure before you buy one.

While prices will continue to decline, as with most new tech products, they will continue to fall as technology advances. A McKinsey research shows that the price of batteries has fallen by 80 percent since 2010. Some anticipate that by 2030, the price of a kWh may be as low as £75. The timing of the UK government’s prohibition on the sale of new petrol automobiles could not be more perfect.

What happens to Electric Car Batteries when they can no Longer Power a Car?

When a battery retires, what happens to it? If you threw it out, you would be wasting the rare resources it contains. It would also be a significant environmental hazard to dump it in a landfill due to soil contamination factors. Alternatively, batteries can be repurposed in one of two ways:

Reusing EV Batteries

It is possible to reuse an electric vehicle (EV) battery once it cannot power a vehicle.

Recycling EV Batteries

Batteries cannot be reused indefinitely, unfortunately. Eventually, they will wear out and need to be replaced. But the rare elements from which they are manufactured might still hold promise for future development. As of yet, there is not a perfect way to recycle them.

Best Electric Car Battery Manufacturers 

The EV battery industry is crowded, as you might imagine, with numerous manufacturers vying for market share. As a result, the vast majority of them are based in Asia. Top 3 selections from our top 3 picks:

  • Tesla is perhaps the most well-known of the inventors in this category.
  • Battery manufacturer LG Chem also has an important position in the battery market. We have a new deal with Tesla.
  • The biggest EV producer in China is currently selling more electric automobiles than fossil fuel vehicles.

Quantum Computing in Cloud Computing: Their Relation and Future Scope

Quantum Computing

Quantum computing is one of the branches of computing that focuses on developing computer technology based on quantum theory. All the data and communication in the computer is in the form of binary numbers. It encodes information in the form of bits that take a value of 1 or 0. Contrary to this, quantum computing uses quantum bits or qubits. A qubit can have more than one value, i.e., 1, 0, or some value between. Therefore, unlike a bit, which has only one value at a time, a qubit can have two states simultaneously. This is called superposition.

Supercomputers were considered the most powerful, but there are certain situations where supercomputers cannot perform very well; therefore, we need quantum computers to deal with such problems.

Types of Quantum Computers

There are many types of quantum computing systems, also known as quantum computers

  • Quantum circuit model
  • Quantum Turing machine
  • Quantum Adiabatic computer
  • Quantum cellular automata

Quantum Computing in Cloud Computing

Cloud computing can be defined as delivering various services like data storage, servers, networking, and databases through the internet. Quantum cloud computing combines the concept of quantum computing and cloud computing.  Cloud Quantum computing can be defined as using quantum computing over the internet. Similarly, cloud quantum computers are the computers that are accessible over the cloud through the internet.

Several companies like Google, Microsoft, IBM, and Amazon using cloud computing are also developing cloud quantum computers to better advantage of computing technology. The network will easily access the cloud quantum computer without having the actual quantum computer. People will have the opportunity to use quantum computer power over the cloud computing environment.

At present, IBM is the only organization that is providing the facility of using cloud quantum computing. Many people are taking advantage of this quantum computer. They allow free access to their 5-qubit machine for everyone. Recently, they have also installed a 17-qubit quantum computer in the cloud. Other companies are also aiming to provide cloud quantum computer facilities in upcoming years.

Relation between Cloud Computing and Quantum Computing

If we talk about the relationship between cloud computing and quantum computing, both are facilitating us. If you don’t have a quantum computer, you can use it over the cloud as different companies have developed their quantum computers and are available over the cloud.

Using a cloud-based quantum computer exponentially increases the benefits of both technologies. By decoding the intricate structure of chemical compounds, quantum computing could aid in the discovery of new medications. Financial trading, managing risk, and supply chain optimization are some of the other applications. Data might be delivered over the internet with significantly safer encryption thanks to its ability to handle more complex numbers.

Applications of Cloud Quantum Computing


Cloud quantum computing can be used for teaching purposes. Quantum physics students can easily understand their concepts and perform experimentation without having the physical quantum computer in their labs or homes.


There is a vast scope of development and advancement in this field. Researchers can perform research, perform experimentation, and test quantum theories using cloud quantum computers.

Future of Cloud Quantum Computing

According to Martin Reynolds, distinguished vice president of research at Gartner, cloud-based quantum computing is more difficult to implement than AI. Therefore the learning curve will be steeper, and the ramp-up will be slower. To begin with, quantum computers necessitate particular room conditions that differ significantly from how cloud providers now construct and manage their data centers.

Quantum computing also necessitates the acquisition of new arithmetic and logic skills by programmers. This is difficult for them because they are unable to use typical digital programming approaches. IT teams must gain specialized skills to understand how to implement quantum computing in the cloud and fine-tune the algorithms and hardware required to make this technology operate.

Despite its drawbacks, the cloud is a great way to consume quantum computing. According to Reynolds, quantum computing offers low I/O yet deep computation. Cloud companies will be among the first quantum-as-a-service providers, as they have the technological capabilities and a significant user base. They will seek methods to deliver the best software development and deployment stacks. If some practical challenges can be overcome, quantum cloud computing will become as far-reaching as AI in the upcoming years.

How System Engineering Help In Risk Management

Risk refers to the possibility of failing to meet overall program objectives within budget, time, and technical constraints. There are two main elements:

  • Probability
  • loss

Risk management entails developing a strategy, identifying and assessing risks, dealing with specific hazards, and tracking progress toward risk reduction. Risk management involves recognizing decisions that may result in future events that cause a terrible impact and devising a strategic strategy and operational risk abatement methods to allow for proper risk management and control. Risk management is a management technique based on identifying and controlling those areas and events in the systems engineering life cycle or process that can cause undesirable changes in the process or result. There are different approaches in risk management:

Inactive Risk Management

In this approach, you do not consider risk factors at all. You do not confront, much less be concerned about, the potential that things may not turn out as planned. It’s easy to say that this isn’t risk management. You agree. However, you prefer to refer to it as poor risk management.

Reactive Risk Management

You try to mitigate the effects of risks that have materialized through post-mortem measures. This could include crisis management attempts to get an organization out of a bind. It is most commonly involved with getting rid of defective products before they are given to consumers, often through inspections.

Interactive Risk Management

Throughout the life cycles of numerous systems engineering activities, you are worried about risk. This means that we pay special attention to requirements like configuration management and project controls to ensure that each phase of the life cycle is as risk-free as feasible in terms of the risk associated with the phase’s product.

Proactive Risk Management

In Proactive risk management, you plan and anticipate risk potentials, then implement systems management actions for the technical direction that control risk potentials throughout all organizational life cycle processes to the extent practicable. In an ideal world, you would manage risks so that any unnecessary risk is improbable to arise.

All these strategies are beneficial in reducing the effects of risk. To apply any of these risk management strategies, we need system engineering processes. System engineering in risk management processes helps to mitigate the chances of risk. It involves the following steps:

  • Risk planning
  • Identification of risk
  • Risk analysis
  • Handling risk
  • Monitoring risk

Risk Planning

We forecast and evaluate risk potential. This entails procedures such as formulation, analysis, and interpretation. We identify potential risks, define alternate courses of action that may mitigate the implications of the various risks, and assess the risks’ influence on these alternative courses of action. Then we evaluate and prioritize them so that we can build plans to minimize unacceptable risks and operational risk control or reduction measures to mitigate the negative consequences of those risks that do occur.

Risk Identification

The process of reviewing project goods, processes, and requirements to identify and document candidate risks is known as risk identification. At both regular periods and following substantial program changes, risk identification should be made continuously at the individual level and through previously established events. Risk assessment should focus on identifying dangers, risks, vulnerabilities, and other factors that could jeopardize work efforts or plans. The following are steps in the risk identification process:

  • The requirements specification is examined and analyzed.
  • The interface requirements specification was reviewed and analyzed.
  • In all appropriate product life-cycle phases, identify the risks associated with cost, schedule, and performance.
  • Other risks to consider are those related to labor strikes, technological cycle time, and competitiveness.
  • Examine the lessons you’ve learned.

At the end of this process, a document is prepared which includes the details like:

  • Risk title
  • Description of risk
  • Strategy applicable for risk
  • The root cause for the risk
  • Related information
  • The team responsible for the risk

Risk Analysis

The process of carefully evaluating each recognized, approved risk to assess the chance of occurrence and consequence of the event (impact) and then converting the results to a corresponding risk level or rating is known as risk analysis.

Technical risks are frequently assessed using risk scales, a related matrix, simulations, and probabilistic risk assessments. In contrast, cost risk is assessed using decision trees, simulations, and payoff matrices, and scheduling risk is assessed using simulations. Approaches to risk analysis are sometimes divided into qualitative and quantitative categories. For risk analysis, you can use either a qualitative approach or a quantitative approach. 

Handling Risk

Risk Handling is the act of identifying and selecting possibilities and implementing the preferred option to minimize risk to an acceptable level within program limits. Assumption, avoidance, control, and transfer are all methods for risk management. For each risk, all four options should be assessed and the best one chosen. After that, an appropriate implementation strategy is determined for that choice. Hybrid solutions with many risk management options, but a single implementation strategy can be established.

Risk Monitoring

Risk monitoring is used to assess the success of risk management operations against established metrics and to offer feedback to the other processes in the risk management process. The outcomes of risk monitoring could be used to update RHPs, develop additional risk management options and methodologies, and re-analyze hazards.

Monitoring outcomes can be utilized to detect new risks, revise an existing risk with a new facet, or revise some components of risk planning in specific instances. Earned value, program metrics, TPMs, schedule analysis, and fluctuations in risk level are some risk monitoring techniques that can be used.

Reliability and Safety Aspects of Autonomous Systems

With increasing advancement in the field of technology, autonomous systems also have gained much attention. Due to their superior hardware and software capabilities, autonomous vehicles such as drones and driverless cars are becoming increasingly popular. Economists expect that demand for electric vehicles will increase in 2021. In upcoming years, there will be millions of electric automobiles on the road worldwide. There is significant progress in the auto industry in producing self-driving vehicles called autonomous cars, thanks to ever-improving technology. Hyundai, Tesla, and Google are the frontrunners in the development of these vehicles.

As they integrate into our society, it becomes critical to ensure that they are always protected, especially in the face of unplanned and unpredictable situations. The recent rapid rise of autonomous systems has enabled a slew of new services and businesses previously unimaginable. However, the unlocked benefits are accompanied by exceedingly computationally demanding mission- and safety-critical application scenarios.

Autonomous systems make decisions based on their knowledge. As their use increases in all aspects of our everyday life, there will be new questions about the public’s role. For example, the technical team and regulators must work together to ensure a safe and ethical environment. deployment; our expectations of them; and the circumstances

We can and should trust them under these conditions.

Standards of Reliability for Autonomous Systems

Expectations and criteria for safety and reliability for autonomous systems are firmly established in international standards, implicit customer expectations, and, not surprisingly, insurance plans. Autonomous systems are also a new industrial industry that is likely to stick around for a long time. In terms of reliability and safety, international standards are the most precise and authoritative prescribers.

The list of current or under-development standards in this field includes:

  • IEC 61508 (Functional safety of Electrical Electronic Safety-related Systems) is related to industrial fields.
  • ISO 26262 is derived from the previous one and is responsible for the functional safety of autonomous systems.
  • IEC 62279 is a modified form of IEC 61508 for railway-related applications
  • ISO 13849 is a standard related to the safety of machinery control systems responsible for safety functions.
  • AC 25.1309-1A is relevant to system design and analysis. It provides background for issues related to aeroplane system design and analysis.
  • RTCA/DO-254 is a design assurance guidance standard for airborne electronic wave hardware

With time, as the technology evolves so rapidly, the reliability standards also need to be enhanced accordingly. Particularly in the field of AI and Autonomous Systems, the reliability standards are under consideration. Measures are being developed to ensure safety and trust in autonomous systems. It is necessary to ensure safe and successful interactions of AS with people and other methods.

Challenges to Reliability and Safety of Autonomous Systems


Any complex system faces the persistent challenge of emergent behaviors that come from interactions within the system. Understanding and managing each of the system’s separate components does not guarantee the system’s safe operation as a whole, and unanticipated emergent features raise the risk of unsafe operation. To deal with this, risk management and make autonomous systems more safe and reliable methods will have to consider the implications and the strategies for prevention and mitigation.

System Oversight

In autonomous systems, they are deployed in complex environments, which increases the number of actors in the system. This increase in number requires overseeing at in much broader level in comparison to previous systems. This result is a significant challenge liability of the autonomous system.

Adversarial Behavior

Individuals may act subversively or aggressively against autonomous systems, especially given their facelessness. Therefore it is necessary to learn from previous technologies.

Testing and Validation

Experimentation results are different for autonomous systems in controlled environments compared to complex environments in which they operate. It is impossible to anticipate all conceivable outcomes that an autonomous system may face when working in the real environment. They may be different situations in the real environment when it fails to work. The variety of events investigated should be risk-based to combat some of this ambiguity.

This entails providing substantially denser coverage in potentially high-risk scenarios, even if they are statistically improbable to occur. A system has two alternatives in the event of an emergency. The first option is for the system to come to a halt to allow for human intervention, while the second option is for the system to make its own choice based on the data available at the time. The ability of human operators to monitor and take control of autonomous systems when they approach their limits or encounter issues must also be confirmed.


A big challenge in the safety of autonomous systems is verification, especially ones that learn and adapt in response to their surroundings. This expands the scope of decision-making beyond the system that was initially created and tested. The opacity of the process, which implies that the software cannot be validated using traditional methods, might make things even more problematic.


Different machine learning algorithms are used to make autonomous systems more reliable and safe. Autonomous systems are protected by using various machine learning algorithms. Using these ML algorithms, the system learns the pattern of the owner with time. Anything that happens against the owner’s pattern algorithm detects it and alerts the owner and demands the user credentials.

Methods for carrying out mathematical demonstrations of properties of machine learning systems are currently being developed in academia. For high-impact, high-autonomy applications, these technologies will have limitations. As a result, new, transparent techniques for machine learning verification will be required. A shift toward operational verification of systems may be required to handle the ongoing learning from that system and those connected to it. This would entail determining where decisions are made and applying focused verification techniques to those aspects.

These approaches are still in the early stages of development. If this is deemed crucial to the safety of particular autonomous systems, considerations about the deployment timeframe will need to be taken.

How well do electric cars hold their value?

Some say that electric cars are the path to the future of transportation, and some argue that the market will diminish in the next couple of years. So, what is an electric car? An electric car is a car running on one or more electric motors that store electricity in their rechargeable batteries. Compared to our traditional vehicles with ICE’s (internal combustion engines), electric cars are much quieter, produce no exhaust emissions, and have near to no emissions overall.

Do Electric Cars Hold Their Value?

Depreciation alludes to the difference between the worth of a vehicle from purchase to sale. Overall, cars depreciate by somewhere between 15% and 35% in the first year. The average new vehicle loses around 60% of its worth after the initial three years. In any case, the vehicle’s depreciation relies upon mileage, condition, and brand of vehicle. Commonly, higher premium vehicles will generally hold their value for longer than standard models.

The sales of electric vehicles have been on a precarious uprise in recent years, with a 180% expansion in sales year on year. Different governments worldwide drive to boycott the sale of diesel and petroleum vehicles by 2030 has expanded the fame of electric vehicles considerably more. But this raises the question, with the rise in the sales of electric cars, do they hold their value?

When electric cars were newly introduced to the vehicle industry, their value depreciated very quickly. There was not enough demand for electric vehicles, and the supply was more than optimal. But as the car batteries have upgraded over the years, and many different brands establish their dominance in the market (such as Tesla), the demand for electric cars has risen drastically hence helping them retain their value for longer.

Premium brands that make electric vehicles hold their value for more. For instance, electric models from Mercedes and Tesla have around 65% – 60% of their worth after the initial three years or 36,000 miles. This is predominantly because owning a premium electric vehicle implies you have the extravagance and high-end quality motors but at the same time are helped by expanding super-low emission zones and fuel costs.

On the other hand, lower-end and more affordable vehicles from any semblance of Nissan, Toyota, and Smart cars are bound to depreciate more rapidly. This is something similar for diesel and petrol variations. These vehicles are more affordable since they utilize cheaper parts, which means they will probably wear more rapidly, which impacts the value of the car over the long run. Due to electric vehicles, most of the car driver’s jobs loos his jobs.

Comparison: Do Electric Cars Depreciate as Fast as Petrol/Diesel Cars?

Top-of-the-line electric vehicles produced by Tesla and Mercedes can hold their value for longer than most other electric vehicles. On average electric vehicles, don’t depreciate any quicker or slower than petroleum or diesel models. Notwithstanding, the depreciation of significant value can change. The general economy and health of the auto business are two important elements while valuing a vehicle. In any case, as the government and vehicle retailers set up incentives to expand electric car deals, you may see that electric cars hold their value for longer.

Usually, assuming you want to reduce expenses in general overall, deciding on an electric vehicle or a hybrid car might be excessively less expensive than purchasing a petrol or diesel vehicle as the running expenses of an electric vehicle are extensively less costly. With most governments encouraging people to buy electric cars, they put on incentives to increase the demand, resulting in less value depreciation over the period, which does not look suitable for petrol or diesel vehicles.

The central aspect of electric cars that really outshines traditional vehicles is that they emit nearly zero emissions, and they are eco-friendly, which benefits our environment. The crucial contrast between traditional ICE vehicles and electric vehicles has to do with the process toward changing the potential stored energy into kinetic (movement) energy. In ICE vehicles, this energy is stored in a chemical structure and is released through a chemical reaction inside the motor, which emits gasses.

On the other hand, electric cars likewise have chemically stored energy; electric vehicles discharge it electrochemically with no burning because of lithium-particle batteries. This implies that there is no fuel being scorched and, this way, no air contamination through CO2 occurring while at the same time driving. They are likewise more productive than fossil vehicles.


By and large, all things considered, electric vehicles will turn out to be more competitive in their costs and insurance in the foreseeable future, which will affect whether electric vehicles can hold their value. With the rise in electric cars, we might see depreciation increment, yet the insurances might be cheaper.

Do Self-Driving Cars use Artificial Intelligence(AI)?

As technology advances, the car industry has used new developments to develop new ways to ease the user (driver). One of them includes using artificial intelligence to make cars self-driving. A self-driving car (also known as an autonomous car or driverless car) is a vehicle that uses a different number of sensors, radars, cameras, and artificial intelligence to travel to destinations without needing a human driver.

Many companies have started to manufacture self-driving cars, such as Tesla, Audi, BMW, Ford, and many more. These companies put their vehicles through many tests to ensure they are eligible to be on the road without making any errors. A car must navigate routes to the predetermines destination without any human intervention to qualify as a fully autonomous car.

How do Self-Driving Cars Work?

Artificial intelligence powers self-driving vehicle frameworks. Engineers of self-driving vehicles utilize immense information from image recognition systems, alongside AI and neural networks, to assemble frameworks that can drive self-sufficiently. The neural networks distinguish patterns in the data, which is fed to the AI calculations.

That data includes images from cameras for self-driving vehicles. The neural networks figure out how to recognize traffic signals, trees, checks, people on foot, road signs, and different pieces of any random driving environment.

do self driving cars use ai

To use an example, Google has also started to develop self-driving cars, which use a mix of sensors, light detectors, and technology is like GPS and cameras, which combines all the inputted data those systems have generated around the vehicle and the artificial system predicts what those objects might do next.

This whole process happens in a matter of milliseconds. Similar to any human driver, the more experience they gain, the better driver they become. This is the same concept for artificial intelligence in the vehicle. The more data it deals with in its deep learning algorithms, the more it will make more choices and faster.

do self driving cars use ai

The following are some basic instructions on how a google car works:

  • The driver sets a destination. The vehicle’s software predicts and ascertains a course.
  • A turning, rooftop-mounted Lidar sensor screens a 60-meter range around the vehicle and makes a dynamic three-dimensional (3D) guide of the vehicle’s present environment.
  • A sensor on the left back tire screens sideways development to identify the vehicle’s position comparative with the 3D guide.
  • Radar frameworks toward the front and back bumpers ascertain distances to obstacles.
  • Artificial intelligence programming in the vehicle is associated with every one of the sensors and gathers data from Google Street View and camcorders inside the vehicle.
  • The AI recreates human perceptual and dynamic cycles utilizing deep learning algorithms and controls activities in driver control frameworks, like steering and brakes.
  • The vehicle’s software counsels Google Maps for early notification of things like tourist spots, traffic signs and lights and other obstacles
  • An override function is accessible to enable a human to take responsibility for the vehicle.

Other Features that Self-Driving Cars have

Google’s Waymo project illustrates a self-driving vehicle that is, for the most part, self-driving. It still requires a human driver to be available yet possibly to supersede the framework when vital. It isn’t self-driving in the perfect sense; however, it can drive itself in ideal conditions. It has an undeniable degree of independence. A significant number of the vehicles accessible to buyers today have a lower level of independence yet, at the same time, have some self-driving highlights. Oneself driving highlights that are accessible in numerous creation vehicles starting in 2019 incorporate the following:

  • Sans hands guiding focus the vehicle without the driver’s hands on the wheel. The driver is yet needed to focus.
  • Versatile cruise control (ACC) down to a stop automatically keeps a selectable separation between the driver’s vehicle and the vehicle in front.
  • Lane-centering steering mediates when the driver crosses path markings by poking the vehicle toward the contrary path checking.

Pros and Cons of Self-Driving Cars

The top advantage promoted via self-driving vehicle advocates is security. A U.S. Division of Transportation (DOT) and NHTSA accurate projection of traffic fatalities for 2017 assessed those 37,150 individuals died in engine vehicle car crashes that year. NHTSA evaluated that 94% of genuine accidents are because of human error or poor decisions, like an alcoholic or distracted driving. Self-driving vehicles eliminate those danger factors from the condition – however, self-driving cars are powerless against different variables, like mechanical issues, that cause crashes.

On the off chance that independent vehicles can lessen the number of accidents, the monetary advantages could be tremendous. Injury impacts economic activity, incorporating $57.6 billion in lost working environment usefulness and $594 billion because of the death toll and diminished personal satisfaction because of wounds, as indicated by NHTSA.

In theory, if the streets were for the most part involved via self-driving vehicles, traffic would stream without a hitch, and there would be less traffic congestion. In completely mechanized vehicles, the tenants could do helpful exercises while driving to work. Individuals who can’t drive because of actual limits could discover new autonomy through self-governing cars and would have the chance to work in fields that require moving.

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Renewable Energy & Cloud Computing: Is Cloud Environmentally Friendly?

Going green is more important than ever in today’s society. Eirikur Hrafnsson, Green Qloud, claimed in 2012 that the internet and cloud computing were contributing significantly to carbon emissions because of filthy energy consumption.

  • Third-party renewable energy sources are now the majority of data centers for large I.T. businesses. Just a few firms have made tremendous efforts to be ecologically friendly and create ecological company goals, such as Amazon, Google, and Facebook.
  • Recently, organizations have realized that moving to a public cloud provides flexibility and scalability while also reducing expenses, thanks to the recent cloud computing boom. It’s possible they don’t know that the cloud improves not only their job but the environment as well. When data is managed and processed on a local server, carbon emissions are substantially increased.
  • By 2020, carbon emissions will have quadrupled to 680 million tons per year from data centers, surpassing the aviation industry. When companies use the cloud, fewer servers need to be purchased, but they are also powered more effectively.
  • The Environmental Protection Agency estimates that data centers consume 1.5 percent of all power in the U.S. by 2020, carbon emissions would have tripled to 680 million tons per year, surpassing the aviation industry in emissions. By transferring I.T. activities to a public cloud provider, carbon emissions and power consumption are reduced considerably.

Better Infrastructure

Data centers in the public cloud are generally placed closer to the facilities that provide them with electricity to reduce the amount of energy lost during the transmission process. A firm like Facebook or Yahoo that constructs traditional data centers typically does not have much choice in terms of location.

Due to their improved hardware configuration, cloud computing data centers also require less electricity to supply backup power and cooling for their data centers. These data centers are meant to be large and efficient in energy usage, allowing for ideal temperature and use.

Higher Utilization Rate

Companies typically operate their own private data centers, which results in low utilization rates because the equipment is acquired and set up in preparation for increases in server demand. Servers are operated at high utilization rates in the cloud, resulting in increased efficiency. Data centers are notorious for wasting resources by leaving equipment idle. Due to the high use of infrastructure, public cloud servers are often 2 to 4 times more efficient than traditional data centers.

Hardware Refresh Speed

Due to the high prices and time required to upgrade servers, traditional data center hardware is often utilized for a lengthy period before it is upgraded or replaced. Cloud gear tends to have a shorter lifespan since it is used more often than traditional servers.

Regular upgrades of public cloud servers are also more cost-effective since new technology improves energy efficiency. Because the public cloud provider will save money by using energy-efficient technology, there will be less energy consumed in the long term.

Reduced Electricity Use

Power, cooling, and lots of electricity are required to maintain traditional data hardware systems. Electricity may be saved by moving simple software programs to the cloud. Moving corporate software such as email, CRM, and more to the cloud (on a national scale) may save enough electricity each year to light Los Angeles for 12 months, according to a case study by the Lawrence Berkeley National Laboratory. 87 percent of these software applications will use less energy if they are hosted on the cloud.

Reduction in Climate Impact

  • As a result of decreased carbon emissions, clouds have improved energy efficiency, which significantly influences climate change. According to Amazon Web Services, “the average corporate data center has a dirtier power mix than the usual large-scale cloud provider.”
  • Its power mix is 28 percent less carbon-intensive than that of other cloud providers. The higher cost of running high-performance equipment in ideal temperatures, this impacts climate control expenses as well. Due to the use of energy-efficient technology and fewer carbon emissions, the cloud avoids these unnecessary expenditures.
  • Amazon Web Services, a cloud provider, aims to expand the use of renewable energy sources in the United States and across the world. We engage with policymakers at all levels of government, including the American Council on Renewable Energy (ACORE) and the U.S. Partnership for Renewable Energy Financing (US PREF).
  • AWS data centers are also powered by wind farms that Amazon has built in the U.S. EDP Renewables, a subsidiary of Amazon Web Services, has signed a deal with AWS to build Amazon Wind Farm U.S. Central in Ohio.
  • A long-term goal for Amazon is to use 100 percent renewable energy by the end of 2016. Amazon’s AWS worldwide infrastructure is now powered by 25 percent renewable energy, but the company aims to achieve 40 percent by the end of 2016 and has a long-term goal of attaining 100 percent renewable energy consumption by 2022.
  • Amazon Chief Evangelist of AWS Jeff Bar argues that cloud computing’s environmental benefits are currently substantial and will only continue to increase in the future.
  • It’s no secret that the cloud is changing the I.T. sector in several different ways. There is no doubting that the cloud’s good influence on the environment is merely one of its many positive attributes.

Cloud Computing can Reduce a Company’s Carbon Footprint

  • 88% of carbon dioxide emissions have been cut in half for companies that use cloud computing. Their server and electricity use has also been reduced by about seventy-seven percent.
  • The software as a service (SaaS) boom has shifted specific programs from individual P.C.s to the cloud to reduce the carbon footprint.
  • This eliminates the need to print numerous copies of documents for different employees. Balance sheets can be maintained in the cloud by accountants. It is possible to add and change pages and sheets at any moment without restriction.
  • It is easy for workers to access and share stored information. Contracts no longer need to be printed thanks to the cloud. Software like DocuSign makes it feasible to sign contracts digitally thanks to cloud-based technology. A virtual version of a business card is available.
  • As a result, firms are becoming more ecologically responsible while simultaneously boosting innovation. This is just the beginning. Renewable energy is frequently used to power cloud data centers, making them ecologically beneficial. Fossil fuel electricity is being replaced by wind and solar power.
  • When Arcadia Power and Agile I.T. teamed together, their data centers and headquarters now run-on wind power, for example. According to the World Resources Institute, the use of green energy instead of fossil fuels is becoming a popular sustainability approach.
  • As a result of the move to cloud-based centers, resources are being conserved. Cloud centers are more energy-efficient than traditional data centers because of technology improvements.

Cloud Computing Increases the Use of Renewable Energy Sources

  • Data centers in the cloud are frequently powered by renewable energy sources, making them green. Fossil fuel-based electricity is being replaced by wind and solar power.
  • Because Arcadia Power and Agile I.T. teamed together, their data centers and headquarters are now run-on wind power, for example. According to the United Nations Environment Program, the use of green energy instead of fossil fuels is becoming a popular sustainability approach.
  • As a result of the move to cloud-based centers, resources are being conserved. Cloud centers are more energy-efficient than traditional data centers, thanks to technology developments.
  • It is easy for workers to access and share stored information. Contracts no longer need to be printed thanks to the cloud. Software like DocuSign and alternative softwares makes it feasible to sign contracts digitally thanks to cloud-based technology. A virtual version of a business card is available.

Cloud Computing means Shared Data Centers, which are Run on Fewer Resources

  • Typically, large organizations that use a cloud server use 60 to 70 percent of the server’s storage space. In contrast, smaller firms prefer to utilize between 5 and 10 percent of their revenue for marketing purposes. So, a single data center may be used by multiple of them.
  • To function at maximum capacity, everyone needs fewer data centers and less equipment. Small businesses need to have access to shared data centers.
  • These data centers are run in the public cloud and are placed near their power supply, so they use less energy to function in the long term. As a result, the wattage of backup power sources is considerably reduced.
  • It is possible to maintain a comfortable temperature in shared data centers while yet utilizing minimal electricity.
  • Servers in the public cloud can be located everywhere there is renewable energy available. A company’s operations function at peak efficiency when it uses the public cloud. To avoid taking up more space than necessary, these files are compressed.
  • The capacity of shared data centers can also be expanded if necessary. It is possible to assign resources according to necessity in the cloud, so computers are only powered when needed.
  • Traditionally, each computer in a data center has a steady supply of electricity. Data centers accounted for less than 1% of worldwide energy use. Optimizing the energy consumption of cloud data centers may be achieved via the application of specific techniques like virtualization, hot/cold lanes, and HVAC modifications.

Cloud Computing Indirectly Decreases Automobile Emissions

  • Indirectly, cloud computing reduces car emissions by facilitating remote work, which in turn reduces commuting times.
  • Fuel savings and car emissions reductions have a direct and obvious impact on the environment.
  • Companies benefit from the efficiency of remote personnel. Reduced personnel numbers translate into reduced resource usage (even down to the disposable paper cups and plastic stirrers for coffee). With less office space, businesses may still function.
  • As a result, smaller workplaces use less energy and heat than bigger ones. Companies may stay productive while also being ecologically friendly by condensing their workspace.


Cloud computing in Robotics: How is Cloud Empowering Robotics?

Cloud computing is the process of storing, processing, analyzing, and storing data and applications over the Internet rather than on your hard drive. Cloud computing refers to the distribution of IT resources on-demand over the Internet for a fee.

Examples of Cloud Computing

  • Hosting and storage in the cloud.
  • E-mail
  • Cloud Backup

Cloud Computing in Robotics

Cloud Robotics is a new discipline of robotics that aims to use cloud technologies like cloud storage, cloud computing, and other Internet technologies to provide robotics with the advantages of converged infrastructure and shared services. Can give Robotic systems significant capabilities thanks to cloud computing, which reduces costs.


A cloud is an internet-connected cluster of computers. Cloud robotics is applying cloud computing resources to improve robotic systems’ collective learning, computational speed, collective memory, and interconnection. Cloud computing benefits businesses by enhancing cooperation and efficiency while also saving money. It entails enhanced data security, increased availability, and increased access to cutting-edge technology.

Other Internet-related features of robotics, such as tendencies toward online sharing of open-source hardware and software, crowd-sourcing of robotics funding, telepresence, and human-based computation, may also fall under the umbrella of Cloud Robotics. Other definitions emphasize the connections between robotics and related emerging topics like the Internet of Things, Web of Things, robot app stores, sensor networks, Big data, and so on.

Cloud robotics is a category of robotics that endeavors to assist robotics by utilizing cloud technologies, including cloud computing, cloud storage, and other Internet technologies. When connected to the cloud, robots can take advantage of the robust computation, storage, and communication resources of a modern data center in the cloud, which can process and share information from multiple robots or agents (other machines, intelligent objects, humans, etc.)

The Information Technology (IT) industry’s current buzzword is “cloud computing.” Cloud computing refers to the use of on-demand computing resources such as software, storage, and infrastructure over the Internet. Although cloud computing has been around for nearly 50 years, technology has only recently advanced to the point that it has become a multi-billion-dollar industry.

What is the difference between Cloud Robotics and Automation?

Let’s look at the distinctions between robotics and automation.

Robots and automation systems by no longer constrained by onboard computational, memory, or software resources. “Cloud Robotics and Automation” is a new model in which robots and automation systems share data and code is based on emerging research in cloud computing, Deep Learning, and Big Data.

Automation uses physical machines, computer software, and other technologies to perform humans perform tasks. Automation refers to using computer software, machinery, or other technology to complete a task that a human would otherwise complete.

Robotics is the procedure of designing, building, and employing robots to perform a specific task.

How Could Computing Empowering in Robotics?

Digital Transformation

That digital transformation is assisting a robot in automating a task while also giving vital data back to help you run your organization more efficiently,” Barga explains. “When people think about robots and automation, they don’t usually consider that story. They understand that it will need a long-term strategy for the services to ingest the data and the analytics they’ll access to create around it to run their business more efficiently. Things start to become extremely intriguing after that.”

Machine Learning

In two places, we employ machine learning—one can found in the onboard computer. A machine learning system is using to improve autonomy during autonomous operation. When a human interacts with the robot, it comes in second place. That’s a good topic to bring up in class. We may utilize that data to strengthen the system’s competence and confidence, so it won’t need to ask for assistance again.”

Cloud Computing Technology

Cloud robotics, which involves the incorporation of cloud computing technology in robots, is gaining popularity worldwide. End-users have begun to recognize the benefits of this novel concept, which uses the Internet to augment a robot’s capabilities, primarily by off-loading computation and providing on-demand services. With this concept aimed at making future robots more productive and efficient, the diverse needs of end-users will meet without sacrificing service quality.

Innovations in Cloud Robotics

Cloud Robotics Innovations discovered that cloud robotics would lead to intelligent robots with higher computing efficiency and lower power consumption. These characteristics will lower manufacturing costs because there will be less hardware, as well as lower emissions.

Cloud robotics innovation has gained traction due to initiatives by large corporations such as Google and IBM and the participation of research institutes in some ongoing projects worldwide. The need to develop robots with high performance and accessibility has been the primary focus of research activities.

Supervised Autonomy

These robots’ heads may be in the clouds, but that doesn’t rule out the presence of a brain. The robots are all self-contained, intelligent units. Mobile robots, particularly those used in intralogistics, must securely navigate warehouses, factories, and distribution centers while avoiding workers, forklifts, and other equipment.

Faster Deployment

The only autonomous mobile robot (AMR) option for material handling and data gathering that deploys in hours rather than weeks and does not require instant integration to demonstrate values is the cloud robotics platform. On-demand automation is the term for it. A cloud software platform effectively runs a fleet of cart-carrying autonomous mobility robots at a third-party logistics warehouse for an automotive company.


Cloud computing is compelling in robotics Cloud technologies have changed the way people live and go about their daily lives, and now they’ve made their way into robotics. Thanks to cloud technology, more powerful robot solutions are becoming available; systems that can handle computationally intensive tasks, offer more power and cognitive collaboration, and vastly expand the amount of data available to share with other machines and humans.

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