IoT for Asset Tracking: Key Aspects
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With 12-year experience in IoT development, ScienceSoft helps build and implement robust IoT-powered asset tracking solutions.
How IoT Can Help with Asset Tracking
IoT for asset tracking helps optimize asset planning, scheduling, allocation, utilization, and maintenance. As a result, businesses can minimize asset loss, misplacement, breakdown, stockout, and excess. IoT-based asset tracking solutions generate up to 40% savings on maintenance and reduce cycle count time up to 90%. Moreover, 79% of supply chain leaders using such solutions record higher revenue growth than their competitors that still use manual asset tracking.
IoT Asset Tracking Market
The global IoT-based asset tracking and monitoring market size is expected to reach $6.7 billion by 2028, rising at a CAGR of 10.7% during the forecast period. The key market drivers include the rise of automation, lower IoT infrastructure costs as well as the growing use of connected devices, IoT-based analytics, and 5G technology.
Tracking the status, location, and movement of raw materials and components, work-in-progress and finished goods for streamlined inventory control and timely replenishment.
Real-time collection and analysis of the status, utilization, performance, condition, and other equipment data for optimized equipment operation and timely equipment maintenance.
Fleet tracking
Monitoring of the vehicle location, condition, driver behavior, fuel consumption, etc. for reduced risks and costs related to vehicle management and telematics.
Facility tracking
Tracking location, condition, space utilization, water and energy consumption, etc. of facilities for their effective planning, maintenance, and optimization.
Tracking the location and usage of medical supplies, tools, equipment, and medications for accurate and safe storage of hospital assets, faster asset search, and streamlined planning of equipment maintenance.
IT asset tracking
Tracking the IT assets like hardware, consumables, and software licenses for full asset transparency, optimized allocation and utilization, timely maintenance and replenishment.
Employee tracking
Monitoring employee location, vitals, and adherence to the rules of workplace safety; detecting potential hazards (pollutants, spills, fires, even overwork) for improved worker safety and health.
Livestock tracking
Collecting real-time data on livestock location, speed, body temperature, etc. for grazing patterns optimization and early detection of heat stress or disease.
Tools We Employ for IoT-Based Asset Tracking
To develop state-of-the-art IoT solutions for asset tracking, ScienceSoft utilizes a range of advanced technologies, including:
Cloud databases, warehouses and storage
AWS
We use Amazon Redshift to build cost-effective data warehouses that easily handle complex queries and large amounts of data.
We use Amazon DynamoDB as a NoSQL database service for solutions that require low latency, high scalability and always available data.
Azure
We leverage Azure Cosmos DB to implement a multi-model, globally distributed, elastic NoSQL database on the cloud. Our team used Cosmos DB in a connected car solution for one of the world’s technology leaders.
Azure SQL Database is great for handling large volumes of data and varying database traffic: it easily scales up and down without any downtime or disruption to the applications. It also offers automatic backups and point-in-time recoveries to protect databases from accidental corruption or deletion.
IoT data analytics and machine learning
Our Apache Cassandra consultants helped a leading Internet of Vehicles company enhance their big data solution that analyzes IoT data from 600,000 vehicles.
We use Amazon DynamoDB as a NoSQL database service for solutions that require low latency, high scalability and always available data.
We use HBase if your database should scale to billions of rows and millions of columns while maintaining constant write and read performance.
By request of a leading market research company, we have built a Hadoop-based big data solution for monitoring and analyzing advertising channels in 10+ countries.
Programming languages
Back end
Practice
19 years
Projects
200+
Workforce
60+
Our .NET developers can build sustainable and high-performing apps up to 2x faster due to outstanding .NET proficiency and high productivity.
Practice
25 years
Projects
110+
Workforce
40+
ScienceSoft's Java developers build secure, resilient and efficient cloud-native and cloud-only software of any complexity and successfully modernize legacy software solutions.
Practice
10 years
Projects
50+
Workforce
30
ScienceSoft's Python developers and data scientists excel at building general-purpose Python apps, big data and IoT platforms, AI and ML-based apps, and BI solutions.
Practice
10 years
Workforce
100
ScienceSoft delivers cloud-native, real-time web and mobile apps, web servers, and custom APIs ~1.5–2x faster than other software developers.
Practice
16 years
Projects
170
Workforce
55
ScienceSoft's PHP developers helped to build Viber. Their recent projects: an IoT fleet management solution used by 2,000+ corporate clients and an award-winning remote patient monitoring solution.
Practice
34 years
Workforce
40
ScienceSoft's C++ developers created the desktop version of Viber and an award-winning imaging application for a global leader in image processing.
Practice
4 years
ScienceSoft's developers use Go to build robust cloud-native, microservices-based applications that leverage advanced techs — IoT, big data, AI, ML, blockchain.
Front end
Practice
21 years
Projects
2,200+
Workforce
50+
ScienceSoft uses JavaScript’s versatile ecosystem of frameworks to create dynamic and interactive user experience in web and mobile apps.
Practice
13 years
Workforce
100+
ScienceSoft leverages code reusability Angular is notable for to create large-scale apps. We chose Angular for a banking app with 3M+ users.
Workforce
80+
ScienceSoft achieves 20–50% faster React development and 50–90% fewer front-end performance issues due to smart implementation of reusable components and strict adherence to coding best practices.
By using a lightweight Vue framework, ScienceSoft creates high-performant apps with real-time rendering.
Mobile
Practice
16 years
Projects
150+
Workforce
50+
ScienceSoft’s achieves 20–50% cost reduction for iOS projects due to excellent self-management and Agile skills of the team. The quality is never compromised — our iOS apps are highly rated.
Practice
14 years
Projects
200+
Workforce
50+
There are award-winning Android apps in ScienceSoft’s portfolio. Among the most prominent projects is the 5-year-long development of Viber, a messaging and VoIP app for 1.8B users.
Practice
11 years
Projects
85+
Workforce
10+
ScienceSoft cuts the cost of mobile projects twice by building functional and user-friendly cross-platform apps with Xamarin.
ScienceSoft uses Cordova to create cross-platform apps and avoid high project costs that may come with native mobile development.
ScienceSoft takes the best from native mobile and web apps and creates the ultimate user experience in PWA.
Practice
8 years
Projects
300+
ScienceSoft reduces up to 50% of project costs and time by creating cross-platform apps that run smoothly on web, Android and iOS.
Data visualization
Practice
7 years
ScienceSoft sets up Power BI to process data from any source and report on data findings in a user-friendly format.
The Challenges of IoT for Asset Tracking
In IoT development since 2011, ScienceSoft knows how to address potential challenges and risks of IoT for asset tracking to make sure your investments pay off.
Challenge #1: Assets’ relevance for tracking
Depending on a company’s size and the number of assets, it may not be worth to track each asset.
Check the solution
Solution: Creating a database of all the company’s assets and deciding on which assets to track. For example, these may be fixed assets worth more than $5,000.
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Challenge #2: Vulnerability to security issues
Connected IoT devices rarely have inbuilt security or consistent update mechanisms, which may result in malware infection, DDoS attacks, damage to the devices, asset data leakage, and more.
Check the solution
Solution: Thorough vulnerability assessment, source code review, penetration testing should be conducted for the IoT-based asset tracking solution before it is launched. Also, an IoT team should make sure that IoT devices are not operating with their default security settings, which poses security risks.
ScienceSoft’s cybersecurity and IoT engineers are ready to design and build highly secure and compliant IoT solutions for asset tracking. Also, we can perform comprehensive security checkups of your entire IT ecosystem, such as risk assessment, compliance assessment, IT security audit, and more.
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Challenge #3: Compatibility issues between different smart devices and IoT solutions
Lack of standardization causes compatibility issues for IoT software and hardware from different vendors.
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Solution: ScienceSoft’s IoT experts recommend API integration as the best option to connect to third-party systems. In our IoT projects, we use the open API approach, which allows us to work with any equipment regardless of the vendor. This approach help avoid risks and restrictions related to equipment supply and maintain the system’s flexibility, enabling you to easily scale up an IoT asset tracking solution if needed.
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Challenge #4: Cloud connectivity risks
Using the cloud technology is a common practice for IoT solutions. But if an IoT solution is based only on the logic of a single cloud app, it creates a serious risk: if the cloud app fails, the entire IoT asset monitoring solution will stop working.
Check the solution
Solution: To protect an IoT solution from shutting off, a mesh networking system should be implemented. This system will enable communication between IoT asset tracking devices even if there’s no access to the main app. We at ScienceSoft leverage this decentralized network in IoT software development, as it allows devices to exchange data directly without access to the cloud.
Thus, the devices are will be able to perform their tasks even if cloud is unavailable.
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According to ScienceSoft’s experience, the pricing of IoT asset tracking software starts from $20,000 - 80,000 and can be as high as $150,000 - $250,000, depending on the solution complexity. |
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These are the main cost factors to take into consideration:
- Types of assets, their number and the expected growth rate.
- IoT hardware (e.g., barcodes, tags, readers) and infrastructure (e.g., network, cloud storage) costs.
- The tech stack and software licenses.
- The number and complexity of a solution’s functional modules.
- The number of platforms supported (web, mobile, desktop).
- The number of different user roles with tailored functionality, the expected number of users.
- The number and complexity of systems to integrate with, including custom or off-the-shelf systems (e.g., ERP, EAM, EHS, CMMS).
- The complexity of the required asset analytics reports and dashboards.
- Solution availability, performance, security, and scalability requirements.
- The sourcing model (in-house vs. outsourced development).
- Team composition.
- Additional IT services like user training and support.
How ScienceSoft’s Expertise Can Help
About ScienceSoft
ScienceSoft is a global IT consulting and software development company headquartered in McKinney, Texas. Since 2011, we offer all-around consulting, implementation, and support services for IoT-based asset tracking solutions to help our customers get full view into their assets, optimize their use, and reduce asset maintenance costs. ISO 9001- and ISO 27001-certified, we guarantee high-quality services and complete security of our customers’ data. If you are looking for expert consulting or development services to implement an IoT tracking system, reach out to our team.