IoT

Just as the internet has transformed businesses and lifestyles in the last twenty years, IoT will disrupt your organization's relationship with its stakeholders. A technology agnostic platform that enables device management, application management, and sensor data management with analytics will jumpstart your engagement with such cyberphysical systems.

The 'Internet of Things' (IoT) symbolizes the next evolution of internet. It is transforming the business playing field, creating opportunities for new sources of revenue, smarter interactions with customers, and greater efficiencies. Yet, IoT presents many technical challenges. By 2025, about one trillion devices are expected to be connected with one another. Networking is one of the toughest development challenges in IoT applications. How do you securely connect intelligent devices via the internet to your enterprise, capture data at the 'point-of-action', and analyze huge volumes of machine-generated data in real-time?

Primarily IoT devices need sensors for converting real world data to a measured value, a processing unit and a communication interface. The intelligence for acting the data could be available locally or in the cloud platform.

After Big Data and Cloud, Internet of Things (IoT) has now arrived as a buzzword, showing the promising future of completely interconnected world with self-driving cars, connected home appliances and real-time collection and analysis of data for instant results. Internet, PCs and Smartphones changed the way we live and work, on the same lines, IoT will change the way we interact with each other and our eco system.

As a business network grows, the complexity of managing the machines and devices housed on it also grows commensurately. With the addition of M2M, such an environment becomes even more complicated. Most organizations are overwhelmed by the day-to-day management of a multi-tiered and evolving M2M platform.

Nimaisoft's Embedded Systems team help businesses leverage IoT technologies to create new services and innovative business models that cut costs, increase productivity and multiply revenues.

Challenges in Developing IoT Services

IoT Protocols-

The next wave of Internet, or IoT is about intelligent, connected devices, supporting hundreds of protocols for successful interaction. These devices communicate with each other (D2D) and data collected from this communication is sent to the server infrastructure (D2S), which then shares the device data (S2S). The data can be provided back to the devices, people, or analysis programs. IoT system can be built on familiar Web technologies, however, the result will not be as efficient as with the new protocols as IoT protocols must produce smaller data overheads, and should be optimized for constrained devices and networks. MQTT, DDS, XMPP and AMQP protocols are gaining popularity, however, there are at least 10 implementations of each, and hence confusion is inevitable. As a result, despite set standards, adoptability has been slow, and many different protocols are being used due to business and technological limitations. There are however several standardization groups and bodies that are actively working to create more inter-operable protocol stacks and open standards for IoT.

Security-

When millions of smart devices are inter-connected, there is a continuous flow of data, travelling between devices, networks, and gateways. IoT is opening the networks that were previously closed, making them more vulnerable to the hackers. Whether in motion, or at rest, data security must be ensured. Most gadgets these days lack the basic protection against hacking, and vendors need to come up with smart solutions. Operators can employ stricter encryption standards that are scalable, efficient and affordable. Another challenge is to educate consumers to utilize security features built into their devices, and users need to keep updating their devices regularly. For end users, security procedures cannot be too complicated, yet they should provide sufficient privacy and protection.

Privacy-

With growing number of connected devices, IoT will generate and store more and more personal information, which will be very attractive for the hackers, leading to more security breaches. Due to the recent NSA revelations, people and organizations are becoming more conscious about maintaining their privacy, and this is affecting the way they are storing the information. To enable development of IoT, international alignment on privacy rules is required. Different countries have different privacy policies when it comes to grasping personal data, and if this alignment is not made, companies will have to choose their selective markets, instead of providing their services all around the world.

Data Flood-

Undoubtedly, IoT will be generating unimaginable amount of data, and existing infrastructure in terms of wireless carriers to the data-centre is inadequate to handle such enormous data volumes. Additionally, this data needs to be processed and stored, resulting in huge infrastructure and maintenance cost. To facilitate data storage, bigger data centers and data farms need to be established, and this will require large investments.

IPv6 adoption-

IoT involves billions of devices, and hence requires billions of new IP addresses. Although we will run out of IPv4 addresses soon, still the adoption of IPv6 is not growing as fast as required and 2013 saw a decline of IPv6 traffic.

Analytics-

To deal with the data, enterprises will have to think beyond conventional business intelligence tools. As an example, in case of medical emergency, the data received from the monitoring devices needs to be analyzed real-time. This data then needs to be stored and reused so that patient care can be improved based on his or her medical history over the past few months. In IoT, data will come in smaller pieces which will not overload the bandwidth, and we can throw away the data which is not required. However, we need to have mechanisms in place to collect only relevant data that is useful for analytics and semantics, and filter the irrelevant data.