What should be considered when developing an app for the Internet of Things?

Internet of Things (IoT) is one of the most popular technologies nowadays and it has brought a significant change in our day-to-day lives. Since the connectivity has improved in the last few years, IoT became more widespread with the passage of time.

IoT technology has gained a lot of traction with the help of growing mobile technology and it is expected to see the surge in the number of IoT applications in the coming years. There were around 15.4 billion internet-connected devices in 2015 and it is expected to reach 30.7 billion by 2020 and 75.4 billion by 2025.

As the demand for IoT devices and applications continues to grow, it is essential to consider what is required for building the Internet of Things apps

Before we discuss what are the important requirements for IoT app development, let’s understand what IoT is.

 

Internet of Things (IoT)

IoT is a network of things (physical objects) embedded with software, sensors and other technologies that can be managed and accessed via the internet using IoT apps and software. The interconnection methods for objects can include wireless links (NFC, Cellular, Bluetooth and Wi-Fi)  and a combination of cables (power supply, coaxial and twisted pair).

IoT has influenced various industries, including healthcare, retail, entertainment, manufacturing and more. IoT devices can range from household objects to industrial tools.

 

Why is IoT important and why should you develop a custom Internet of Things Application?

 

Seamless production, customer satisfaction and maintenance are the pillars of business performance. IoT applications can help optimize business processes, improve conversion rates and make the business stand out of the competition.

Here are some of the benefits of IoT applications:

  • Improved flexibility
    With IoT applications, people can stay connected to any device anywhere and anytime. It is possible to operate multiple things/tasks from one device. From turning up the volume of the TV to controlling thermostat and dimming the lights, every device can be connected for streamlined control.
  • Improved productivity
    IoT facilitates the monitoring, processing and controlling of multiple processes and optimizes different operations, thereby improving efficiency and productivity.
  • Collecting rich data
    Data is the most significant weapon for every organization. IoT models and methods are being used by organizations nowadays to collect a huge chunk of data about business products and customers. By gathering this information, organizations can perform analysis to improve the quality of their products and earn more revenue.
  • Reduced operational costs
     IoT technologies can benefit organizations to reduce operational costs and maximize profit. For example, the use of IoT devices in the manufacturing industry can enable the monitoring and tracking of equipment. The data captured by IoT devices can help reduce downtime by gathering useful data related to manufacturing. Using IoT solutions can also reduce power consumption, therefore, the entire cost for an industry can be reduced.

As you can see that the number of connected devices and IoT apps will keep growing, it is essential to understand what should be considered when developing an Internet of Things application.

 

What should be considered for IoT App Development?

For an IoT App Development, components and concepts can be broken down into the following categories:

  • Hardware
  • Data Capturing
  • Data Transmit
  • Data Filter
  • Computation and Action
  • Business Intelligence, Analytics and Reporting

Hardware

The Internet of Things refers to the connection between the virtual world and devices. Smart devices, including smartphone-controlled coffee machines and Google Home, contain connectors and physical sensors used for measuring physical characteristics.

Physical elements identified by IoT devices get converted into the data, fed back into the device and on the connected device, usually referred to as the internet.

Therefore, the hardware behind IoT is as crucial as the software that facilitates data capturing and transfer.

The complete hardware for an IoT device can be categorized into the following components:

  • Hardware Boards
  • Firmware
  • Edge Computing
  • Sensors

Hardware Boards

The hardware board for IoT applications should be selected based on the following factors:

  1. Connectivity Capability
  2. Sensors Capability
  3. Size and Computation Power
  4. Cost and Availability
  5. Date of Manufacturing and Expiry

IoT hardware boards and modules are at the center of every IoT device. IoT hardware comprises a wide range of devices for routing, sensors and bridges. You need to consider buying a hardware board that fits the exact requirements of your IoT project.

Let’s discuss each of the above characteristics based on which hardware board selection needs to be done.

1. Connectivity Capability
Network connectivity is a significant characteristic of every IoT device. Communication between devices is done locally and then they upload data via cloud-based services. Some devices interact wirelessly using Bluetooth, 802.11 (Wi-Fi), cellular networks, NFC, RFID or low power wide area network (LPWAN) technologies, including SigFox, NB-IoT or LoRa. Wired communication is suitable for stationary devices that can be installed in industrial control apps, smart buildings or home automation.

  • Bluetooth:
    It is a wireless technology standard used to exchange data over short distances (short-wavelength UHF radio waves in the ISM band from 2.4-2.485 GHz). Bluetooth technology is categorized into three types: Bluetooth, BLE (Bluetooth 4.0, Bluetooth Low Energy) and iBeacon.

     

    1. Bluetooth: Earlier, Bluetooth was considered as a black hole and battery drainer. This Bluetooth technology is now a success story of the past marked by a bulky cell phone. The technology is insecure, battery draining and complex to pair.
    2. BLE (Bluetooth Low Energy): Initially introduced by Nokia, BLE is presently used by all significant operating systems, including iOS, Windows Phone, Android, Blackberry, OS X, Windows 8 and Linux. BLE technology uses less energy and is fast while maintaining the communication range.
    3. iBeacon: It is a simplified communication technique based on the Bluetooth technology used by Apple. Beacons are small Bluetooth transmitters. Apps installed on the iPhone device listen to the signal transmitted by beacons and send a response when the phone comes into the range.
  • Wi-Fi:
    It is a wireless local area network that uses the IEEE 802.11 standard via 2.4 GHz UHF and 5GHz ISM frequencies. Wi-Fi offers internet access to devices within the range. It comes with universal smartphone capability and is well controlled and protected. It is suitable for many Internet of Things connections but those connections usually connect to a cloud server, not connected to the smartphone. Due to its high power consumption, Wi-Fi is not recommended for battery-enabled devices.
  • NFC (Near Field Communication):
    Using electromagnetic induction between two loop antennas situated within each other’s near field, NFC forms an air-core transformer. It runs within the widely available and unlicensed radio frequency ISM band of 13.56 MHz on ISO/IEC 18000-3 air interface at rates from 106-424 kbit/s.It comprises an initiator and a target where the initiator actively creates an RF field to power a passive target (unpowered chip called “tag”). It allows NFC targets to take form factors, including stickers, key forbs, tags or battery-less cards. NFC peer-to-peer communication becomes possible when devices are powered on.
  • RFID (Radio Frequency Identification):
    Radio Frequency Identification uses electromagnetic fields wirelessly for identifying and tracking tags attached to objects. It is quite similar to barcoding where the data from a label or tag is captured by a device that feeds the data in a database. However, RFID has many advantages over the barcode asset tracking system. Barcodes must be aligned with an optical scanner but RFID tag data can be gathered outside the line-of-sight.
  • LPWAN:
    LPWAN is not a standard, it’s a broad term that encompasses different protocols and implementations. LPWAN technologies run on small and cheap batteries for years and operate over a wide operating range, typically more than 2 km.LPWAN is an excellent connectivity option for big buildings or cities for asset tracking, smart grid and smart lighting. It can work efficiently in situations where devices have to send small data over the wide-area while maintaining battery life.

Consider selecting the hardware board based on the type of network connectivity your IoT device and application requires.

2. Sensor Capability
Sensors are components that evaluate physical variables and convert them into electrical signals. They can vary in functionality and can be used to measure a wide range of variables, including humidity, pressure, temperature, smoke, light, sound, vibration, water-flow, GPS position, speed and altitude.

Determine the type and number of sensors and output components that your IoT device and app requires when selecting the hardware board.

Here are some of the sensors commonly used in the Internet of Things devices:

  • Temperature Sensor
  • Pressure Sensors
  • Gas Sensor
  • Smoke Sensor
  • Accelerometer and Gyroscope Sensor
  • IR Sensor
  • Proximity Sensor

3. Size and Computation Power 

When selecting the hardware board for your IoT device, the size of the board plays a crucial role. Whether you are developing a small smart bulb or a an IoT-based smart camera, make sure to choose a hardware board based on the device.

You should also consider whether your IoT device needs to be hardwired for power, or requires a portable power source such as a supercapacitor or a battery.

If your device needs a battery, you need to understand the weight, capacity and size requirements for the battery. Also, whether the battery must be rechargeable, discarded or replaceable after it gets drained.

4. Cost and Availability

The cost of the hardware comprises the cost of the outlay for the hardware and its associated components, for example, sensors. You should also consider their on-going operating costs, including maintenance and power costs in the form of defective components and replacing worn parts.

Consider licensing fees for some device drivers or components as well. Buying available off-the-shelf development boards is more economical than fabricating custom hardware boards.

Also, check the availability of the type of hardware board you are looking for in the market. Compare the various types of available hardware boards and pick the one that fits your project requirements.

5. Date of Manufacturing and Expiry

Some hardware boards might come with some date of manufacturing and expiry. So, it is essential to check the dates of manufacturing and expiry before buying any hardware board.

For example, if you buy any hardware board that may expire after a year and you could not complete the development work, buying that board would be worthless.

Therefore, consider the expiration dates before purchasing any IoT hardware board.

Firmware

 

Firmware is a software program that is programmed on a hardware device and allows them to interact with other hardware systems.

Developing firmware for IoT devices can be quite challenging and requires technical expertise and a wide range of techniques and tools.

Here are some of the languages that are commonly used for firmware programming:

  • C
    The C programming language is one of the excellent choices when it comes to embedded systems programming. The low-level access and low power usage provided by the language are significant factors behind C’s acceptance as the best-embedded systems programming.The statically typed language offers high speed as compared to other programming languages. C language’s loose data typing policy makes it ideal for embedded systems programming.
  • C++
    C++ provides access to not only low-level system resources but also ensures that memory stack is free from unwanted system calls. It allows you to use inline functions for the replacement of macro definitions.C++ is an ideal choice for embedded system programming because of its ability to use constructors and overloaded functions. It has a namespace feature that does not let your program crash if it has any naming conflicts issues.
  • Java
    Java is not only a good programming language for desktop applications, but it can be also used for embedded systems programming. Due to its stability feature and availability of many dev tools, Java programs are highly recommended by embedded systems developers. Writing embedded system programs with Java makes it easily portable across various IoT platforms.Using Java, developers can isolate the crucial portions of the embedded applications from the rest of the code. Also, Java programs are fast and can run flawlessly even when backed by old generation hardware.
  • Rust
    Rust is one of the modern programming languages used to build embedded systems. It is an ideal choice for embedded systems due to its higher-level concepts, guaranteed safety, typestate programming style and zero-cost abstractions.It’s powerful static analytics guarantees that unused components of the application won’t consume resources of the system. Rust incorporates the concurrency model that ensures no two threads can share the same state during runtime. Developers can integrate Rust into their C++ or C programs seamlessly. Whether you are programming SBCs or small microcontrollers, Rust lets you port your embedded system’s code across a wide range of systems.
  • Python
    After gaining popularity in the web and enterprise world, Python has gained momentum as the top embedded systems programming language in the last few years. Due to its readable and concise coding style, Python is the right choice for embedded systems for new developers. Since it is an interpreted language, it will need a Python runtime when python programs run. It provides the best solution for writing automation tests for a real-time embedded system.Python facilitates processing images and parsing logs due to which Python excels at developing embedded systems for processing data in real-time.

You can use the above programming languages to develop firmware for your IoT devices based on your needs and requirements.

While considering the right language for firmware development, it is also essential to look at the firmware updates that is one of the significant components of IoT app development.

Firmware Updates

Firmware Updates are often required to enhance security, fix bugs or add new features. Many internet-enabled devices check for new firmware on a regular basis and download and install updates automatically.  On the other side, some device manufacturers ask the user to visit their website for downloading and installing updates manually.

Earlier, when IoT technology emerged, people had to retrieve the device, disassemble it, connect it to the computer, program it again, assemble it back together and return the device to the field. With the growth and improvements in IoT technology, the industry is now shifting to Over-the-air (OTA) firmware updates.

OTA firmware updates are significant for IoT success as they can drive security of connected devices, reliability and extensibility. As soon as a bug that affects security or business logic is discovered, firmware can be updated right away.

If there are any few features to be developed, push them to deployed things. Developing firmware right the first time could be complicated. From security to networking to business logic, you need to handle everything at some point on remote devices. The ability to leverage OTA firmware updates can help you eliminate these issues, but it may introduce some complications.

Therefore, it is recommended to find the team of best IoT developers who can provide firmware development with fault tolerance and high availability.

Edge Computing

 

It has been predicted that over 30 billion IoT devices will be deployed worldwide by 2020; therefore, the amount of data to be stored in the cloud is beyond the imagination. The processing power required for deriving any value out of that data cannot be estimated easily. One of the best ways to handle the data outside of the cloud is at its “edge”.

According to LogicMonitor Survey, cloud adoption is suitable when 83% of enterprise workloads are being handled in the cloud. But, traditional cloud computing has some drawbacks:

  • Performance Issues
    IoT apps depend on real-time actions. But, the processing speed of a cloud-based app relies on the distance between the server location and the device itself.
  • Increased Operational Costs
    Operational costs may grow when the amount of data shared and produced increases.
  • Data Security Threats
    Since the data is transferred back and forth between a device and the cloud, the risk of security gets increased.

On the other hand, the term “edge computing” defines the data computation that occurs where the data is produced, i.e., at the edge of the IoT network.

Instead of requiring a centralized, remote cloud to perform all the work, the data is managed and stored locally, i.e., either near to the network node or on the IoT device itself.

Let’s understand how edge computing works with the help of an example.

Every IoT sensor/device generates tons of data every second. In cloud computing, the data is transferred quickly to the unified, central cloud database where it’s processed and stored. If any action is needed, the central server responds back to the device upon obtaining and analyzing the gathered data.

Though the entire process hardly takes a second to complete, there can be some conditions when responses might be interrupted or delayed. It may happen due to the weak internet connection or because the data center is far from the device.

But, in the case of edge computing, there is no need to send the data gathered by IoT devices anywhere. Instead, the nearest network node or the device itself processes the data and can respond when action is required.

Storing and processing data at the edge reduces the need for an abundance of cloud storage. Also, you can filter out unwanted information and keep the backup of only relevant data. So, the overall cost of infrastructure and data transfer can go down.

With Edge Computing, IoT devices do not need to depend on the internet connection and can operate as a standalone network node.

Sensors

 

Nowadays, sensors can be found everywhere from homes to shopping malls, workplaces, hospitals and warehouses. They are a significant part of every IoT product.

Sensors are devices that identify and respond to changes in the environment. Inputs can be provided from a wide range of sources, including temperature, pressure, motion and light. Sensors output useful information and can exchange data with other connected systems.

They have the ability to warn you of problems before they become major issues, enabling businesses to avoid expensive downtime and conduct predictive maintenance.

Sensors are available in different sizes and shapes. Some of the sensors are purpose-built and comprise various built-in sensors, helping you evaluate and monitor multiple data sources.

Following are some of the popular IoT sensors with their use cases:

  • Humidity Sensors
    These sensors are used to evaluate the amount of water vapor in the atmosphere of other gases and air. They are usually installed in vents, air conditioning and heating systems in both residential and industrial sectors.
  • Temperature Sensors
    Temperature Sensors are used to evaluate the amount of heat energy in a specific source, detect temperature changes and convert them into the data. Machines used in manufacturing usually need devices and environmental temperatures to be at specific levels.  For example, the soil temperature is a crucial factor for crop growth within the agriculture sector.
  • Proximity Sensors
    Proximity Sensors are used for detecting the presence of nearby objects without physical contact. These sensors emit an electromagnetic field and identify changes in the return or field signal. Proximity Sensors can detect the motion between a product and the customer to find the customer’s interest in a particular product.
  • Pressure Sensors
    Pressure sensors can detect changes in liquids and gases. The sensor detects changes in the pressure and communicates them to connected devices. They can be used in the manufacturing of water systems because they can easily detect fluctuations in pressure.
  • Level Sensors
     Level Sensors can detect the level of various materials, including liquids, granular and powder substances. Industries such as water treatment, oil manufacturing and food and beverage manufacturing factories use level sensors.
  • Gyroscope
    Gyroscope sensors are used to evaluate the angular velocity or rate, usually defined as the measurement of rotation and speed around an axis. Its use cases include camera-shake detection systems, car navigation and motion sensing for video games.
  • Accelerometers
    Accelerometers are used for detecting an object’s acceleration, i.e, the rate of the object’s velocity change with respect to time. Its use cases include smart pedometers and monitoring fleets. They are also used as anti-theft protection that alerts the system when the stationary object is moved from its location.

Once the IoT hardware is ready, the next step is to manage data capturing.

Data Capturing

Since an IoT device generates a massive amount of the data, you need to decide what and how much data should be captured based on your business needs and requirements.

Data to be captured depends on the following scenario:

  • Application-specific Data Capturing
    If you only require data specific to your IoT application, an application-specific data capturing strategy can be applied to the IoT device. IoT devices can then capture the required data and the IoT app can process the data for further insights and information.
  • Event-based Data Capturing
    Data generated from the sensors are defined as sensor events. Therefore, event-specific data capturing is done if you want to capture the data generated from the sensors embedded in your IoT device.
    Sensor Events can be:
    • Motion
    • Activity
    • Temperature
    • Light
    • Vision
    • Sound
    • Smell

    If any of the above sensor events occur, the data is captured and used by the IoT application to take action corresponding to that information.

  • Time-based Data Capturing
    Time-based data capturing is done when your IoT device needs to capture the data on a specific time basis. For example, there is no need to capture the real-time soil moisture data from sensors installed within the agriculture field every time. You may need soil data on a daily basis instead of capturing it every second to make improvements.So, you can implement time-based data capturing if you need to gather the data based on a specific scheduled event.
  • User-generated Event Data Capturing
    User-generated Event Data Capturing can be done when the data needs to be captured if a user performs some event. For example, if you are developing an IoT device that should perform an action or gather data when the user touches the device or pushes the button. In this case, the data is collected based on the event generated by the user.

Once the data is captured, the next step is to identify how much data needs to be stored on the local buffer or cache.

Local Buffer/Cache

As we have mentioned above in the article that there will be around 30.7 billion internet-connected devices in the market by 2020, generating tens of zettabytes of data that must be stored and handled efficiently. People have a lot of assumptions in their minds that all this data would be simply stored on the cloud. But, the storage solution is actually far more complicated.

Think about the volume of data generated in transportation alone. Every autonomous car is expected to generate around 2 PB (Petabytes) of data each year. It is possible for cars to push all the data into the cloud in real-time.

Even if we have 5G data networks, there may not be enough bandwidth to manage that amount of data transfer in real-time. Therefore, connected cars and other devices today use onboard local storage to collect and cache data until it can be moved to the cloud via a high-speed network.

The amount of local storage required by your IoT device depends on your data retention policy. Once you understand how much data you need to acquire, how much and how often you will send data to the cloud, you can evaluate how much local storage will be needed as temporary storage to serve as a buffer in case you lose connectivity to the cloud or to perform calculations.

If your IoT device has to be offline for some time, you will have to define for how long it will run without the connectivity and how much data needs to stored locally.

Embedded flash drives, cards and SSDs are the perfect local storage solutions for IoT devices.

Data Transmit

Communicating essential physical parameter data and transmitting it via the internet is one of the essential tasks in the world of IoT.

Data captured by the IoT device requires a direction to be transferred, updated, managed, stored, acknowledged or exported to other devices. These tasks can be done via suitable protocols.

You need to select the right communication medium for your IoT device and protocols for data transmission between the devices and the user.

Communication Methods for Data Transmission

  • RFID (Radio-Frequency Identification System)

It uses labels or tags attached to objects you need to identify. Two-way radio receivers-transmitter also called readers or interrogators send a signal to the label and read its response. Readers usually communicate observations to a system running RFID middleware/software. RFID tags can be active, passive or battery-assisted passive.An active tag contains an on-board battery and transmits the Id signal periodically. On the other hand, a battery-assisted passive (BAP) comprises a small onboard battery and gets activated in the presence of an RFID reader.Examples: Inventory, Road Tolls

  • NFC (Near-Field Communication)

It is a set of short-range wireless technologies that require a distance of 10cm or less. Operating at 13.56 MHz on ISO/IEC 18000-3 air interface, NFC runs at rates ranging from 106 kbit/s to 424 kbit/s.It makes peer-to-peer communication possible provided that both peer devices are powered.Examples: Action Tags, Access Control and Smart Wallets

  • WiFi

Using WiFi, electronic devices can exchange data wirelessly over a computer network using high-speed internet connections.Examples: Tablets, Routers

  • GSM (Global System for Mobile Communications)

It is a digital cellular technology used to transmit data and mobile voice services. Terrestrial GSM networks cover around 90% of the total world population. GSM satellite roaming has also expanded its service access to locations where terrestrial coverage is unavailable.Examples: Smart Meter, Asset Tracking

  • Bluetooth

It is a wireless technology standard used to exchange data from mobile and fixed devices over short distances, creating personal area networks with high-security levels.Examples: Smart speakers, fitness trackers

  • LoRWAN

It is a point to multipoint networking protocol that uses Semtech’s LoRa modulation scheme. It facilitates long-range bidirectional communication with low power consumption, enabling operation for up to 10 years on the same battery.Based on an open protocol approach, the LoRaWAN is managed by the LoRa Alliance that oversees the development of the protocol and ensures interoperability within all LoRaWAN networks.

It is a low-power and low-cost IEEE 802.15.4 based specification for a series of high-level communication protocols used to create personal area networks. Designed for small-scale projects that require a wireless connection, it’s applications include home energy monitors, traffic management systems, wireless light switches and short-range consumer and industrial equipment.

  • Z-Wave

It is a wireless communication protocol, primarily designed for home automation. It is a mesh network that uses low-energy radio waves for appliance-appliance communication.Z-wave system can be managed via the internet from a smartphone, computer or tablet and locally via a wireless keyfob, smart speaker or wall-mounted panel with a Z-wave gateway.

  • LiFi

It is a mobile wireless technology that uses light instead of radio frequencies for data transmission. It holds the potential to solve the challenges faced by 5G. With the ability to transmit at multiple gigabits, LiFi is interference-free, reliable and more secure than radio technology.

Protocols for connecting IoT devices in a distributed network

  • MQTT (Message Queue Telemetry Transport)

MQTT is used to target lightweight M2M communications. As an asynchronous publish/subscribe protocol, it runs on top of the TCP stack and aims to connect embedded networks and devices with middleware and applications.It is an ideal messaging protocol for M2M communications and the IoT and can provide routing for small, low memory and power devices in low and vulnerable bandwidth networks.MQTT has a broker (server), containing topics. Each client is a publisher that sends information to the broker at a specific topic and a subscriber who gets automatic messages every time, when there will be a new update in the topic one, is subscribed to.Since it is lightweight, it is suitable for M2M, WSN and eventually IoT devices where actor nodes and sensors interact with applications via the MQTT message broker.

  • OCPP (Open Charge Point Protocol)

Open Charge Point Protocol is an application protocol that enables the communication between a central management system and electric vehicle charging systems. It can be used to communicate a 24-hour prediction of the local available capacity to the charge spot operator.

  • AMQP (Advanced Message Queuing Protocol)

AMQP emerged from the financial industry and can use different transport protocols but assumes a fundamental transport protocol like TCP. It offers asynchronous publish/subscribe communication with messaging.The benefit of AMQP is its store-and-forward feature that facilitates reliability even if network disrupts. Defining a wire-level protocol, implementations of AMQP can interoperate with each other.

  • REST

APIs are tightly linked with IoT because they allow IoT devices to expose connected devices securely to customers, go-to-markets and other applications in the It infrastructure. Since APIs connect the Internet of Things, including smart grids, cars and thermostats to your ecosystem, it is essential to deploy API that is scalable and secure.RESTful APIs are used in the modern web and the data gets transferred using XML or JSON over HTTP. REST APIs use HTTP specification methods to perform various actions, including POST, GET, DELETE and PUT.REST is considered a good model for IoT because every device can easily provide its state information and can have a standardized way to read, create, delete and update that data.

  • Thread (Network Protocol)

It is a low-power mesh networking technology for IoT devices, intended to be future-proof and secure. It allows device-to-cloud and device-to-device communications and connects hundreds of devices. Thread networks have no single-point-of-failure and therefore, can reconfigure when a device is removed or added. Since it is IP-based, it allows devices to interact directly with the cloud and other IoT products.

Data Filtering

An IoT device generates an abundance of data that must be analyzed and examined. As more data is generated and moved faster, finding and analyzing the data seems harder. IoT data contains tremendous business value acros various industries. However, with the influx of information comes the need to better filter out the data noise, false positives and duplicates.

Data generated by IoT devices can be filtered out based on:

  • Application
  • Compliance

Application-specific Data Filtering

If you want to filter data specific to your IoT application, identify whether your application requires mission-critical data or sampling data.

For example, if a Satellite gets launched and moves into space and sends its data to users examining it on the ground. The data gathered by sensors equipped in a satellite is mission-critical and the loss of data can result in the failure. Therefore, mission-critical data needs to be handled carefully in real-time.

Another example of mission-critical data is the data captured by machinery. Data generated by machinery is also critical data that should be managed with diligence. Unleashing the mission-critical data buried in production machinery can help manufacturing companies enhance manufacturing yield and overall equipment efficiency.

On the other hand, you may only require macro/sampling data that is not required in real-time and can be filtered based on the requirements.

For example, if a sensor installed within the agriculture field to detect the soil moisture is not expected to report different moisture readings within a few seconds. Therefore, you don’t need to capture and transmit the data in real-time. Instead, you can filter the data and analyze it on a daily or weekly basis.

It depends on the application whether it requires mission-critical data or sampling/macro-level data.

Compliance-specific Data Filtering

Sometimes, an IoT app needs to filter data while ensuring compliance and security.

For example, IoT-enabled cameras installed on the roads to analyze the speed of vehicles and spot accidents should capture the data irrespective of individual faces and identities. IoT devices should only feed the data that is required and useful for decision-making.

IoT devices also need to ensure that no confidential financial information should be stored or exchanged when managing finance-related data.

Moreover, private usage logs should not be kept for a long time. Imagine that there is a facial recognition based attendance system in an organization that allows employees to get entry into office by analyzing their face data. IoT-enabled face recognition system should only authenticate a person by matching their facial data, but not store that data on the cloud.

It is essential to implement compliance-basis data filtering when it comes to the security and privacy of the data.

Computation and Action

 

The final step is to apply computation and action on the data generated from IoT devices. Computation process can be categorized into the following steps:

  • Workflow Execution
    You need to define a workflow for the data captured by IoT devices. For example, if the temperature under which a product should be kept gets increased, users can receive a notification immediately. There should be a defined workflow for the IoT-enabled system so that actions could be taken efficiently.
  • Maintenance
    IoT devices require maintenance from time to time in order to meet the growing requirements. There should be some plan for maintaining the IoT sensors and devices.In case, IoT sensors stop sending the data to the cloud due to which IoT application and the device stop working. As a result, it could obstruct some business operations and analysis.Therefore, an action plan should be created in a way that the owner should get a notification when IoT sensors stop sending the data so that maintenance could be done on time and before app users face any difficulty.
  • Analysis and Action
    IoT devices and applications should be developed in a way that they should perform a specific action based on the data gathered through IoT sensors. For example, if temperature sensors send the notification about the reduction in the level of temperature, the smart air conditioner should automatically control the temperature level.
  • Control, debug and troubleshoot remotely 
    While developing the IoT application and device, ensure whether your application should be able to control, debug and troubleshoot devices remotely.If you want to control the data generated by IoT devices remotely, you need to look for the methods for remote control IoT-devices and various interaction protocols. For example, smart home automation devices allow users to control devices installed in their homes remotely.
  • IFTTT (If This Then That)
    IFTTT is a web-based service that is used to create chains of simple conditional statements, known as Applets. Automation in IoT devices can be accomplished via applets that can connect different applications to execute tasks automatically.IFTTT can be implemented in different applications. For example, if the doorbell rings, lights get blinked Or lights should turn on during sunset.

Analytics, Reporting and Business Intelligence 

Business Intelligence (BI) and Data Analytics enable individuals and companies to extract the insights captured and transmitted between IoT devices. These valuable insights can be utilized to bring improved services to market and enhance the efficiency and performance of their business.

Reporting and Analytics are crucial for every business that is looking to derive value from IoT technology.

Following are some of the actions that both small and large companies can take with the help of BI and Analytics:

  • AI/ML Models Upgrades
    With informative insights gathered about the performance of IoT devices, companies can identify whether there is a need to upgrade the AI/ML models.  You can change the algorithms to improve the machine learning models of your IoT device to enhance their performance.
  • Predictive Analysis
    BI provides an opportunity to explore patterns and predict trends. BI facilitates predictive analysis by monitoring data streams from connected sensors in systems or complicated machinery.For example, with BI and predictive analysis, it can be possible to discover when any component of escalators may fail, allowing the responsible authorities to perform preventive maintenance.
  • Improvements in Product Roadmap
    Based on the analytics and business intelligence reports, it can be identified whether the entire product works seamlessly or not. It helps in enhancing the product roadmap for future products and enabling companies to develop robust IoT products.
  • Enhanced User Experience
    It is also possible to discover if IoT device users can interact with IoT devices seamlessly or not. If you find that users are facing difficulty interacting with the IoT device and application, you can improve the user experience to retain the potential users.

Author’s Bio

Akash Takyar
Akash Takyar
CEO LeewayHertz
Akash Takyar is the founder and CEO at LeewayHertz. With the experience of building over 100+ platforms for startups and enterprise allows Akash to rapidly architect and design solutions that are scalable and beautiful.
Akash's ability to build enterprise-grade technology solutions has attracted over 30 Fortune 500 companies, including Siemens, 3M, P&G and Hershey’s. Akash is an early adopter of new technology, a passionate technology enthusiast, and an investor in AI and IoT startups.
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