Big Data Technologies and Tools

An organization is all about the data it beholds and to make a decision that is valid for years, a massive amount of data is required. This brings us to today’s topic ‘how to handle data influx with Big Data‘ and what are pointers that you should know about Big Data.

Power of the Big Data can be used to elevate the business to new levels and capture market opportunities. Big Data is the term which is used for massive data. As the data inputs are received from a variety of sources, it is diverse, massive, and beyond the capacity of the conventional technologies.

Such quantum of data requires computationally advanced skills and infrastructure to handle it. Once equipped with the appropriate infrastructure the data must be analyzed for patterns and trends. Such trends and patterns aid in formulating marketing campaigns.

Following are some industries that are already ahead in leveraging Big Data for regular operations:

• Government organizations trace social media insights to get the onset or outbreak of a new disease.
• Oil and gas companies fit drilling equipment with sensors to assure safe and productive drilling.
• Retailers use Big Data to track web clicks for identifying the behavioral trends to adjust their ad campaigns.

Below we have listed few Big Data Technologies and big data tools that ought to be aware of

1. Predictive analytics

This technology helps you to discover, assess, optimize, and deploy predictive models, which will improve business performance by moderating business risks.

2. Stream analytics

Stream analytics analyzes the varied data in different formats that come from disparate, multiple, and live data sources. This method helps to aggregate, enrich, filter, and analyze a high throughput of data on a regular basis.

3. NoSQL database

NoSQL database is having an exponential growth curve in comparison to its RDBMS counterparts. This database offers increased customization potential, dynamic schema design, scalability, and flexibility which is a must for storing Big data.

4. In-memory data fabric

This technology lets you process data in bulk and provides low-latency access. Also, it distributes data across SSD, Flash, or dynamic random access memory (DRAM) of a distributed computer system.

5. Data Virtualization

If you require real-time or near real-time analytics to be delivered from various big data sources such as Hadoop and distributed data sources, data virtualization is your best way out.

6. Data integration

Data integration includes tools that enable data orchestration across solutions such as Apache Pig,  Apache Hive, Amazon Elastic Map Reduce (EMR), Couchebase, Hadoop, MongoDB, Apache Spark, etc.

These tools are discussed in detail for you to understand below:

a) Apache Spark

Apache Spark is the fastest and general engine for Big Data processing. It has built-in modules for SQL support, graph processing, streaming, and machine learning. It supports all major Big Data languages including Java, Python, R, and Scala.

The main issue with data processing is the speed. A tool is required to reduce the waiting time between the queries and time taken to run the program. Apache Spark complements to computational computing software process of Hadoop but it is not the extension of the latter. In fact, spark uses Hadoop for storage and processing only.

It has found its utilization in industries which aim to track fraudulent transactions in real time like Financial institutions, e-commerce industry, and healthcare.

b) Apache Flink

Apache Flink was introduced by Professor Volker Markl- Technische University, Germany. Flink is a community-driven open source framework which is known for accurate data streaming and high performance.

Flink is inspired by MPP database technology for functioning like Query Optimizer,  Declaratives, Parallel in-memory, out-of-core algorithms, and Hadoop MapReduce technology for functions like User Defined functions, Massive scale out,  and Schema on Reading.

c) NiFi

NiFi is a powerful and scalable tool with the capacity to process and store data from a variety of sources with minimal coding. Also, it can easily automate the data flow between different systems.

NiFi is used for data extraction and filtering data. Being an NSA project, NiFi is commendable in its performance.

d) Apache Kafka

Kafka is a great glue between various systems from NiFi, Spark, to third-party tools. It enables the data streams to be handled efficiently and in real time. Apache Kafka is an open source, fault-tolerant,  horizontally scalable, extremely fast and safe option.

In the beginning, Kafka was a distributed messaging system built initially at LinkedIn, but today it is part of the Apache Software Foundation and is used by thousands of known companies including Pinterest.

e) Apache Samza

The main purpose to design the Apache Samza is to increase the capabilities of Kafka and is integrated with the features like Durable messaging, Fault Tolerant,  Managed State, Simple API, Processor Isolation, Extensibility, and Scalability.

It uses Kafka for messaging and Apache Hadoop YARN for fault tolerance. Thus, it is a distributed stream processing framework which comes with a pluggable API to run Samza with other messaging systems.

f) Cloud Dataflow

With a simple programming model for both batch-based and streaming data processing tasks, Cloud Dataflow is a native Google cloud data processing integrated service.

This tool cuts your worries about operational tasks including resource management and performance optimization. With its fully managed service, resources can be dynamically provisioned to maintain high utilization efficiency while minimizing latency.

Final Words

All of these tools contribute to real-time, predictive, and integrated insights which are exactly what big data customers want now. For gaining a competitive edge with big data technologies, one needs to infuse analytics everywhere, develop a speed differentiator, and exploit value in all types of data.

For doing all this, an infrastructure is required to manage and process massive volumes of structured and unstructured data. Thus, data engineers require the above mentioned tools to set patterns for data and help data scientists examine these huge data sets.

How to build a career in Data Science

Today, data scientists are one among the highest paid professionals. Technology is soon advancing and it is necessary that you constantly pay attention to upgrade your skills and expertise.

Tech giants such as Google, Facebook, Apple etc, all of them are looking for data science experts to build intelligent and path-breaking products.

If you are planning to become a data scientist, then you need to be well-versed in some programming languages. In this blog, we list the top 11 skills that you must possess to become a successful data scientist.

1. Education

Data scientists are usually from the highly educated crowd in the college. As a matter of fact, 46% of them have PhDs while 88% of them have a Master’s degree.

You could be from any stream like social science, physical science, computer science,  or statistics in order to be a data scientist. The common field of studies are as follows:

• Mathematics and Statistics (32%),
• Computer Science (19%)
• Engineering (16%).

A degree course in the above fields helps you to develop skills you need to analyze big data. It is highly recommended to obtain a Master’s or Ph.D. after successful completion of the Bachelor’s program. To transit into the data science field, you will require to pursue your master’s degree in Mathematics, Data Science, Astrophysics or any such related field.

2. R Programming

R programming is specially designed for data science needs. Any problem in the field of data science can be solved with R. Currently, 43% of data scientists use R to solve statistical problems. Therefore, it is recommended to learn R.

However, R is tricky to learn especially if you have already mastered a programming language. An online learning program should be taken up to learn R.

3. Python Coding

Along with Java, C/C++, Perl, Python is the most common coding language and is perfect for data scientists. Around 40% of the data scientists use Python as their major programming language. Python is a versatile language and can be used in almost all the steps of the data science processes.

With Python, you can easily import SQL tables into your code and also process various forms of data. Further, it allows you to create your own datasets.

4. Hadoop Platform

This is not a pressing requirement but it is highly preferred in many cases. Also, if you have experience with Pig or Hive or familiarity with cloud tools such as Amazon S3, you will be preferred over other applicants.

Why Hadoop platform is important?

There might be a situation when the volume of data to be processed exceeds your system’s memory and you will require to send data to different servers. In such a situation, you can use Hadoop to transfer your data to various points. Also, Hadoop can be used in data sampling, data exploration, data filtration, and summarization.

5. Apache Spark

Apache Spark is faster than Hadoop with the same big data computation framework. The reason why Apache spark is faster than Hadoop is that Spark caches the computations in memory while Hadoop reads and writes to disk.

Apache Spark helps data scientists to handle complex unstructured data sets and saves time by processing the data faster. It can be used on one machine or a bunch of machines, at once.

6. SQL Database/Coding

SQL stands for Structured Query Language. SQL is a programming language which enables you to carry out operations like delete, add, and extract data from a database. Also, it helps in transforming database structures and carrying out analytical functions.

For becoming a successful scientist, you need to be proficient in SQL. SQL will help you to access, communicate and also work on data. It has brief commands that can help you lessen the amount of programming you need to perform. Additionally, it will help you comprehend relational databases and boost your experience profile.

7. Data Visualization

For a data scientist, it is essential to visualize data to make it easier to understand. This can be done with data visualization tools such as d3.js, Tableau, ggplot, and Matplottlib. These tools can convert data into easy formats.

Data visualization is the need of the contemporary corporate world because of the insights delivered. These insights indicate which business opportunities to grab and how to stay ahead of the competition.

8. Machine Learning and AI

Machine Learning can give you an edge over others as with this you can transform the way data science is functioning. Most data scientists are not proficient in this field. To stand ahead of others, you must learn decision tree, supervised machine learning, logistic regression, etc. Read here for more information on which Machine Learning Algorithm to pick. 

A proficiency in Machine Learning helps you in solving complex data science problems that are based on predictions.

Other examples of advanced machine learning skills that you should consider are Unsupervised machine learning, Natural language processing, Outlier detection, Time series, Recommendation engines, Survival analysis, Reinforcement learning, Computer vision, and Adversarial learning.

9. Unstructured data

A data scientist must essentially be able to work with unstructured data. Basically, the unstructured data are undefined content that can not be put into database tables.

For instance, customer reviews, videos, blog posts,  video feeds, social media posts, audio etc. Such heavy data is difficult to sort because they have no order.

Unstructured data is also referred to as ‘dark analytics’ because of its complex nature. Ability to comprehend and discern unstructured data from several platforms is the prime attribute of a data scientist. It helps you interpret the insights that are useful for decision making.

Apart from the above mentioned technical skills, following non-technical skills will help you to achieve your goals faster.

10. Intellectual curiosity

Curiosity provides you with the thirst to learn something new every day. As a data scientist, you will counter new problems every now and then, at this moment, curiosity will motivate you to find solutions to your problems.

On average, data scientists spend about 80% time in discovering and preparing data. In order to keep pace with the evolving world of data science, you need to keep learning.

11. Communication skills

Data scientists make complex data understandable for normal people which is why it is essential for them to have smooth communication skills. With fluent communication skills, they will be able to explain their technical findings to non-technical teams such as Sales or marketing department.

Thus, with these 11 skills, you will be able to launch your career as a Data Scientist. Even if you are someone who is planning to shift technologies, just spend some time to learn programming languages such as R, Python and the Apache suite and you will be in a good position to start off a career in data science.

Blockchain Technology in Supply Chain Industry

Have you ever felt the need to retrace the origin of your mobile phone that you can’t keep away even for an hour?

Or from where your fav clothes came?

The stores that sell these products are the last anchor to a long thread of supply chain which begins when your clothes were just wool balls.

Every industry has its own supply chain but the most relatable industry is the clothing industry.

Right from the raw material supplier to the retailer, there is a sophisticated supply chain that in simple terms means the back-end industry.

A supply chain management includes the planning and the execution of all the processes included in getting the finished products.

It is a network of individual entities, businesses, organizations, technologies as well as resources that are put together in the manufacturing of a product. It is essential to properly plan and implement a supply chain as it holds benefits like increased sales and revenues, reduced frauds and overhead costs, acceleration of production and distribution, and quality improvisation.

It might seem easy theoretically but practically implementing and maintaining supply chain is a very hectic job. As the business grows, the supply chain tends to become redundant given that the interconnectivity among the integrated elements of the supply chain might not match the efficiency level to the enhanced scale. Such inefficiency may pose a major threat to the business operations and may lead to a breakdown.

Advanced technologies like AI and Machine Learning are used in Supply Chain Management (SCM) to overcome such inefficiencies that are hazardous to the businesses. But blockchain technology can prove as a total game changer in the supply chain management for the aid it provides in record keeping and tracking.

Blockchain – A better-automated alternative

Blockchain Technology can be used to resolve many challenges of the Supply Chain industry such as complex record keeping and tracking of products. With Blockchain Technology, a better-automated alternative to administer the centralized databases is offered.

Apart from the record keeping and tracking, there are several other ways in which the Blockchain Technology aids the functioning of a supply chain.

1. Origin Tracking

Due to a very high volume of transactions and many elements in the supply chains, even the companies with very advanced workforce lose the track to transactions. These inefficiencies attract additional overhead costs and sometimes loss of customer data costs unpleasant customer relationship and brand name dilution.

Blockchain-based supply chain management provides provenance tracking and record keeping which makes the information fetching very easy with embedded sensors and RFID tags.

The product history can be traced right from the origin to the present situation at any point in time. Also, such accuracy in provenance tracking can be utilized to detect and prevent frauds even in complex supply chains.

2. Cost Reduction

A survey conducted by APQC and the Digital Supply Chain Institute (DSCI)  of supply chain workers unveils that more than one-third of people think that reduction of costs is the topmost benefit of Blockchain in Supply Chain Management. This is because of the real-time product tracking offered.

With Blockchain, extra cost can be reduced while maintaining the security of the transactions. Also, the middlemen and intermediaries in the supply chain are eliminated.  

This reduces the risks of frauds and duplicity of products and enhances accurate record keeping and savings

3. Building  Confidence

With multiple participants in the complex supply chain,  building trust in the system is essential for smooth operations.

For instance, the integrity of the records should be such that when a participant in the supply passes the information to the next level participant, the receiver should be able to rely on the information without a doubt.

Also, the regulatory authorities, being stakeholders should be able to rely on the information and records. The blockchain is characterized by immutable record keeping which prevents the information from tampering on all levels.

Benefits of using Blockchain in Supply Chain Management

1. Interoperability

The Blockchain technology allows data to be interoperable which eases the data sharing process among the manufacturers, retailers, vendors, and contractors. The transparency in data sharing helps reducing delays and conflicts.

Also, it prevents goods from getting stuck in the supply chain cycle because each product can be tracked in real-time which makes the chances of misplacements rare.

2. Scalability

Surplus capacity is available at ease with this technology. It offers scalability with which large databases can be accessed from multiple locations around the world.

While maintaining high standards of security the users have the ability to customize according to the data feed. The most lucrative feature of this is ‘selective permissions’ which means the participant will be able to view the data for which he has the permission.

The permission to allow the data to be accessed can be granted explicitly to the participants. Apart from these, there are others benefits of adopting Blockchain technology in supply chain management:

• Lessen or eliminate fraud and errors
• Advance inventory management
• Reduce courier costs
• Minimize delays in paperwork
• Identify any issue faster
• Build consumer and participant trust

Final Words

Blockchain has the potential to spin the supply chain industry for good. Blockchain has the best use in the supply chain management and is expected to grow at a very fast pace in the coming future. The key to properly implement and operate a supply chain is to keep transparent and end-to-end connectivity.

In order to reap the benefits of applying Blockchain in the supply chain industry, corporates should begin to embed the newer system today. For higher rewards and improved performance, the bulky paperwork and complex databases need a replacement and there is no better substitute than Blockchain.

Vishwas Mudagal – Winner of the Manambassador Award

We are super proud and happy to announce that our CEO, Vishwas Mudagal has won the Manambassador Award by PinkLadder. The Manambassador award identifies male champions in the society who have taken considerable efforts to create an inclusive work environment for women and encourage them to take up leadership roles.

The PinkLadder is India’s first comprehensive career enhancement ecosystem for women professionals and it has been founded by Karthik Nagendra and Soujanya Vishwasnath.

By being recognized as a male champion by PinkLadder, Vishwas Mudagal is one among those few men who envision a better place for women and encourages them to be ambitious and potential leaders. As an inclusive family man, highly followed influencer on social media, and as a CEO of a woman-led technology company, Vishwas Mudagal is setting an example for men to step up and set a stage for women to succeed.

This was an emotional moment for Vishwas and he went on to dedicate this award to our MD and Founder – Sonia Sharma who has been his inspiration throughout. To quote in his own words, Mudagal goes on to say –

 

Honored to receive the Manbassador Award for being Male Champion of Diversity and playing my part in the industry as an evangelist for inclusion, gender equality, and women empowerment.

Thank you PinkLadder and  Karthik Nagendra for recognizing my efforts and giving me this award! I dedicate this award to Sonia Sharma my co-founder and life partner, for being my inspiration and guiding light.

We need more women like you who empower everyone around us. Blessed to have you as a friend and partner in this wonderful journey! Hoping to take this to the next level!

Vishwas Mudagal is also a LeanIn India mentor where he coaches women for leadership roles and also encourages them to get back into the workforce.

Our team at GoodWorkLabs is immensely proud to have such progressive leaders who encourage us, appreciate us and treat us all as equals.

Vishwas Mudagal inaugurates IDFC Bank’s Whitefield Branch in Bangalore

We are super excited to announce that today our CEO, Vishwas Mudagal inaugurated IDFC bank’s branch in Whitefield, Bangalore.

IDFC is one of India’s leading bank and is highly technology driven. In today’s highly competitive banking sector, IDFC is highly customer focused and ensures every banker enjoys a smooth customer experience. It’s all about convenience and with the right mix of technology, IDFC bank is all set to create an unparalleled banking experience for its customers.

We at GoodWorkLabs feel extremely happy to be part of this inauguration ceremony and wish the very best for their future expansion plans across India.

Here are some glimpses of the event:

Ranked as one of the Top Mobile App developers in India for 2018

We are happy to announce that Clutch has named GoodWorkLabs as one of the top app developers in Bengaluru. The excitement just doubled when Manifest, Clutch’s sister website also recognized us among their top app developers in India for 2018.

Our DNA here at GoodWorkLabs: beauty, scalability, agility, and innovation are what helps us stay ahead of the curve. Our team thrives on resolving complex challenges, building innovative software, and helping change the world through technology and design. GoodWorkLabs offers a multitude of services, ranging from software development and UI/UX to IoT and big data technologies, but we strive for excellence with every project and partner.

This recognition comes from Washington, D.C.-based research and reviews firms – Clutch and The Manifest. They rank a variety of small and mid-market businesses by combing through qualitative and quantitative data, such as market presence, prior experience, and client feedback. These analyses are then compiled into rankings of companies both throughout industries and countries to provide relative comparisons of work and service.  

Customer Reviews and Testimonials

By being selected as one of the Top App developers in the country, it just speaks volumes of the quality of work we deliver to our clients.

When we asked one of our clients about their experience of working with GoodWorkLabs, this is what they had to share –

“GoodWorkLabs managed the whole project, and I found that aspect of their services to be exceptional. The fact that GoodWorkLabs’ team contributes actively to the work, are passionate about my ideas, and want to learn more about the journey is what’s most impressive.” 

Read the full review

“My expectations in terms of quality, service, and cooperation were far exceeded. The dollar-to-dollar value was tremendous. There are times when you receive more than what you paid for, which was the case here,” echoed another client. “There may be vendors offering the same level of work, but one of the things that stood out for me was their level of service and approach to the customer’s need. GoodWorkLabs is focused on what has to be done. If there was an issue, they did everything in their power to make sure that it was fixed quickly.”

Read the full review

Our team at GoodWorkLabs is very proud of the work we do and the software solutions that we provide, and we sincerely thank Clutch and our clients for their support and recognition of our commitment to excellence and to quality service.

If you are interested in reading more reviews that detail our involvement and experience, see our Clutch profile. We welcome you to connect with us if you are interested in working together on a future project or hearing more about our approach and experience!

As a Google Certified Developer Agency, GoodWorkLabs is hosting a community meetup on Actions on Google for Google Assistant on the 14th of July at GoodWorks CoWork.

This is the next wave of technology and through this event, you will get a chance to be trained by experts, work on code labs and build innovative actions for Google Assistant.

Build Actions that Solve for India

Join us to build innovative and unique actions for Google Assistant that are locally relevant, taking into account aspects of language, devices, battery consumption and connectivity, solving problems for India in the space of agriculture, education, healthcare, FinTech, e-commerce etc.

Register for event

This is an event tailored especially for developers who want to learn new skills and work on AI technology. As a Google Partner, GoodWorkLabs aims to nurture the developer community and conduct workshops on Google technologies.

Register now and join us in building actions that solve for India at our swanky coworking space in Whitefield.

We are very excited to announce that our CEO, Vishwas Mudagal will be joining Facebook COO Sheryl Sandberg’s Lean In – He For She Program in India as a Mentor & Executive Committee Member. This is an initiative that aims to empower women to achieve their ambitions.

Vishwas is known to change lives with his leadership and through this He for She mentoring program, he aims to bring a change by being a male champion of diversity and gender equality.

“This initiative is close to my heart because women development across the cross-section of the society has been one of the key areas where I want to bring a change. In this direction, I truly believe male inclusion in women development is critical,” says Vishwas Mudagal, CEO of GoodWorkLabs.

Further, Mudagal added, “Men have an important role to play in reaching equality & everyone benefits when they do. Children with involved fathers are happier, healthier & more successful. Couples who share responsibilities have stronger marriages. Diverse teams & companies produce better results. Leaning in is not just the right thing to do, it’s the smart thing to do.”

In this video, Vishwas Mudagal speaks more about his thoughts on the LeanIn India initiative.

We are super happy and proud that GoodWorkLabs is part of this social cause. Through this initiative, we want to set an example and urge every man to work towards gender equality.

How IoT is Fostering the Age of Smart Manufacturing

Despite the IoT’s decade-old origin, the technology in recent years has had an exceptional run that could only be paralleled to that of Midas’ Touch. Although Midas’ gift eventually became a curse to him and those around him, IoT has been nothing but a boon to those that use it. There are a great many verticals that have embraced the power of IoT and yet there are many more that still shy away from this relatively new technology. Manufacturing is a sector that has been on both sides of the spectrum when it comes to the implementation of IoT. There are very few companies that employ IoT as part of their manufacturing initiative, even though most industry leaders expect over 75% of the global manufacturing to include technologies such as IoT to boost visibility in the supply chain. This is the basis for the concept termed as Smart manufacturing.

What is Smart Manufacturing?

Smart manufacturing is an aspect of manufacturing where the latest advancements in IT and manufacturing are employed in cohesion to improve productivity and enable flexibility to address the growing needs of a global market. This involves the use of both advanced software as well as hardware which include fields like robotics, AI, IoT etc. This use of technology impacts both the physical aspect of turning raw materials into products and all the logistics and financial concerns associated with the various processes. There is, therefore, a steep demand for adaptability, on the infrastructure, enterprise and workforce levels. This is one of the major reasons why smart manufacturing is not being employed on a comprehensive level even amongst companies that have adopted it to a certain degree.

The IoT factor in Smart Manufacturing

We are approaching a phase called industry 4.0 which could also be defined as the fourth industrial revolution. Here to survive manufacturers must conform to the various technological advancements that dictate the industry or eventually perish. IoT is one of the largest disruptors in the world on almost all fronts of the enterprise. Manufacturing, in particular, relies a lot on this technology to create better visibility and flexibility in their manufacturing processes. As a matter of fact industry, 4.0 is a term that closely associated with the application of IoT in manufacturing and with good reason.

Automation is a staple amongst most large-scale manufactures. Even if in its rudimentary form, automation helps manufacturers keep up with the growing markets and their ever-increasing demands. While automation is a highly productive technology whose roots date back to the 17th century, today’s industry demands connectivity amongst the machines to enable effective management of the production cycle. Data as always is key and IoT helps gather and manage this data to allow the production chain to function without any lags. Furthermore, it also facilitates scalability and improved visibility within the chain.

Does Manufacturing Really Need IoT?

At the moment things are pretty straightforward. However, in the years to come manufacturing sector and associated processes are going to become more complex, particularly on the logistics side of things. As globalization becomes more and more of a factor, companies, particularly the large manufacturers will have to come up with a swift, cost-effective and efficient way to manage their logistics needs.

As more and more technologies and devices are incorporated by manufacturers the entire process is going to get a lot more complex and data generated therein will be a vital aspect of the growth and productivity of manufacturers. So at some point in the near future, IoT will be implemented to make the best out of production and logistics. By connecting devices, companies will be able to make the best out of the data they generate and this data can be leveraged to enhance the production cycle and improve various aspects of the production cycle.

The Challenges

Despite the known prospects of employing IoT in manufacturing, most of the industry is still unapproving of it. Around 70% of the manufacturing industry believes that IoT is not really a necessity at this point for their business. Most of this stems from the ignorance of company leaders. Most of them fail to see the use of IoT beyond a data standpoint. And when it comes to data people find it a vague prospect which costs more than its actual value for their businesses.

The second issue that stops people from adopting IoT is a misconception that the technology will only help large-scale companies and would be a drain on smaller companies’ funds. This is patently untrue as the adoption costs of IoT and the time taken for implementing it are all going down as advancements and research continue. The introduction of open source solutions also provides a good opportunity for manufacturers of all sizes to implement IoT and that too without having to spend much on dedicated engineering staff to monitor the technology. Not only does IoT address immediate issues of the company, it entails several long-term benefits that manufacturers can benefit from by effectively leveraging the technology.

Lastly, one of the biggest hindering factors for the implementation of IoT is the security concerns. The worldwide cyber attacks in recent years have manufacturers bothered about the security risks that this technology could be prone to. This, while a legitimate concern, can easily be tackled by exploring holistic security strategies. There are several cybersecurity providers who will offer the best security solution for IoT systems operating in the manufacturing sector.

Could IoT be the Answer to Colonizing Other Planets?

There is a lot of banter going on these days about colonizing Mars and the Moon. While it is true that we are closer than ever before to actually take the first steps towards such a program, the possibilities of actually establishing a human colony on the Moon, let alone Mars are pretty bleak according to scientists who have been researching this for decades. Yet all hope is not lost. For most parts of the whole grand scheme of colonizing other planets humans would probably be the last to be sent. It would be robots, rovers and many other automatons that will go first and prepare a planet for our arrival.

On paper, this seems like quite a plausible idea, as we already have plenty of rovers on both Mars and the Moon. In the crazy times known as the 1950s, the Americans were determined that they’d set up a fort on the Moon by 1969 and that it would house mainly soldiers. However, things are not that simple or straightforward or in their case based on a child’s fantasy. The rovers that currently reside on these objects, are merely there for reconnaissance and relaying the data derived therein. We are really far away from any working technology that could terraform a planet and prepare a habitable base. Also, we have to remember that these robots and devices have to last for years. If Mars One, SpaceX and Elon Musk’s plans are anything to go by, we might have all the technology required to successfully establish a Mars or Moon base in the next 10 years. And if such an event comes to pass, IoT will be a crucial technology that will help with the coordination of all these devices.

Internet of Rovers

Every single rover on the Moon and Mars are autonomous and are capable of performing several actions on their own. However, they need to be guided on which quadrant on the surface they need to analyze and so on. When the colonization process starts, getting all the machines to communicate would be an ideal option. While we’d still be providing the coordinates and all other data, drilling, mining construction and so on. Even if astronauts are around, there needs to be an internal communication between the machines. An IoT system will allow them to communicate smoothly and coordinate the processes without any delay in work.

The Long Trip

It takes anywhere between 5 to 10 months to get to Mars. That is a long time for humans to be in transit and travelling at 32,000 Kms per hour is not going to make the experience any more bearable. Tempers may run high, all sorts of issues may pop up between the astronauts, even leading to fights. So, it would be wise to keep them engaged with various social and recreational activities and minimize their involvement in the operations of the spaceship. While navigation is to a great degree automated in space crafts, there are several other processes that are usually done by the astronauts, be it monitoring or physically interacting. With IoT, most of these processes could be done by the devices themselves without drawing the attention of the humans. Furthermore, the use of wireless technology could save a lot of space and weight in the spacecraft allowing more room for payload. There are several research programmes that currently focus on this particular aspect.

XBee ZigBee Modules

Digi International an M2M developer worked with NASA a few years ago to test the potential of IoT in spacecraft and eventually in colonizing Mars. Digi helped NASA incorporate its XBee ZigBee Modules into their Sub-Orbital Aerodynamic Re-entry Experiments (SOAREX). The aim was to test the effectiveness of wireless operations in space. This is a substantial step for future long-term missions such as the one planned for Mars. These technologies will allow astronauts and researchers to gather much more data during burns, landings, lift-offs, and a myriad of other processes. By incorporating IoT a lot of devices can be allowed to function wirelessly freeing up space for payload or decreasing fuel consumption. Both are essential for long trips such as the one to Mars.

Landing On Mars

Even if things go as planned and according to schedule, there are several issues that need to be addressed.  By now we have gathered tons of data from the various space missions and flybys from as early as 1972. Yet with all this data, we’ve just scratched the surface. There is a lot of information that the four Mars rovers Sojourner, Opportunity, Spirit and Curiosity have sent back to us. The data sent by Curiosity in particular opened up the prospects for habitable conditions on Mars and in two years Mars 2020 will be bound for the Red Planet to further analyse the resources and topography and climate. This is where IoT will come in handy. If a cumulative effort were to be taken by the many space programs that are bound towards mars, IoT could be employed to mine out more than we have in the past 45. The application of IoT in robotics has been quite evident in for the past decade or so, including the Robonaut which is now wifi enabled and capable of connecting with the various devices on the ISS. So such a network of connected machines on Mars or the Moon even could speed up our journey to the far reaches of our solar system. And the potential for colonization could be further explored in detail.

From where we stand today, machines are the key. No human has stepped foot on a celestial body since 1972, ironically the year that the Mariner 9 probe was launched to orbit Mars and study the planet, a job it continues to do even today. So, it is machines that will help reboot our space touring days, and it is technologies like IoT and AI that will help us achieve this.