IoT & ML-based Energy Management Solution

IOT FOR ENERGY MANAGEMENT

IoT & ML-Based Energy Management Solution

The team developed software for IoT energy management, specifically tailored to monitor wind turbines and manage energy production.

#IoT

#Energy

#ML

Client*

A leading business in the renewable energy industry for over 20 years, specializing in wind energy and overseeing a vast network of wind turbines across multiple regions.

*We cannot provide any information about the client or specifics of the case study due to non-disclosure agreement (NDA) restrictions.

Project in numbers

duration

Ongoing project

team

14 specialists

The team involved in the project

industry

Energy

solution

Data analytics

technologies

JavaScript, React, Redux, Python, FastAPI, Apache Spark, Kubernetes, Docker, AWS, PostgreSQL, Grafana

Services

1 x Business analyst

1 x Project manager

1 x Solution architect

3 x Back-end developers

1 x Front-end developer

1 x Embedded developer

1 x ML developer

1 x DE developer

1 x DevOps Specialist

2 x QA engineers

1 x Stakeholder’s SME

Challenge

Build an IoT energy management solution empowered with ML algorithms for real-time monitoring and predictive analysis of wind turbine performance. The main goal is to prevent system malfunctions that could cause power outages and costly repairs.

Solution & functionality

The team came up with an IoT & ML-driven energy management software solution that predicts energy production. An advanced platform provides real-time updates on the status of each wind turbine based on the information accumulated from meteorological sensors and turbines.

Programmable logic controllers (PLC)

We utilized programmable logic controllers (PLCs) to gather data from sensors placed across the wind turbines. They monitor various operational metrics, like wind speed, turbine rotation speed, temperature, vibration, and torque, process the data and provide a precise overview of the wind turbine’s current performance, identify faults, and energy production efficiency. Additionally, system detects deviations, like an unexpected temperature rise or increased vibration — to prevent damage, it triggers alarms or shuts down the turbine. Such timely maintenance and malfunction prevention ensures balanced energy production and extends equipment lifespan.

Data visualization

To visualize data, our project team chose Grafana dashboards. We created customized actionable charts for IoT energy management displaying data like daily power output, turbine locations, weather patterns, and predicting future trends. Thanks to these visualizations operational managers have access to a real-time overview of turbine performance, while maintenance teams can quickly address turbine issues.

Data lake

The client needed a robust data lake, as they operate wind turbines across various regions. Our developers created a central repository to collect and store data from all turbines, regardless of their location, including structured, unstructured, and semi-structured data such as logs, sensor readings, and images. Data is collected from the PLCs and then stored and processed using AWS IoT Core and Lambda functions. Large datasets can be processed simultaneously, which greatly supports predictive maintenance and accelerates analysis and reporting.

Error prediction

Leveraging data science and MLOps, we developed a predictive model that evaluates various factors influencing turbine health, such as vibration and temperature levels, and performance metrics. This model continually learns from incoming data and enables the operational managers to detect warning signs of failures early. Upon identifying them, the energy management control system sends alerts to the maintenance teams so that they proactively address the issues before they cause breakdowns.

Analytical reports

The energy management system can generate analytical reports based on the historical and real-time data to provide insights into wind turbine performance. This data helps identify well-operating turbines and those needing maintenance. Also, by analyzing performance trends and external factors like weather, the system suggests ways to optimize energy consumption, determine ideal times for energy harvesting, manage storage, reduce costs, and streamline maintenance.

Results and business value

The team successfully implemented IoT in energy management, providing the client with a scalable energy management control system.

up to 6%

increase in energy production

18%

reduction in maintenance and repair costs

26

critical threats prevented

Benefits for client

The solution helps prevent system malfunctions that could cause power outages and costly repairs. As a result, the client achieved 18% reduction in maintenance and repair costs and up to 6% increase in energy production.

Related cases

Need assistance with a software project?

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    What happens next?

    An expert contacts you after thoroughly reviewing your requirements.

    If necessary, we provide you with a Non-Disclosure Agreement (NDA) and initiate the Discovery phase, ensuring maximum confidentiality and alignment on project objectives.

    We provide a project proposal, including estimates, scope analysis, CVs, and more.

    Meet our experts!

    Viktoryia Markevich

    Relationship manager

    Samuel Krendel

    Head of partnerships

    Odoo Implementation for ERP Processes with a 16% Surge in Online Sales

    Odoo ERP for eCommerce

    Odoo ERP Implementation with a 16% Surge in Online Sales

    Timspark offered Odoo ERP services to replace the client’s outdated, bespoke ERP system, execute CRM integration, and develop an AI chatbot to foster the company’s digital transformation.

    #eCommerce

    #Odoo

    #ERP

    Client*

    Our client is a US-based industrial equipment and components retailer with 50 employees. It is strategically positioning itself for business expansion within the fiercely competitive realm of e-commerce.

    *We cannot provide any information about the client or specifics of the case study due to non-disclosure agreement (NDA) restrictions.

    Project in numbers

    duration

    7 months

    team

    13 specialists

    The team involved in the project

    industry

    E-commerce

    solution

    Odoo ERP for Ecommerce

    technologies

    Odoo, JavaScript, React, Python, Google Ads API, PostgreSQL

    3 x Business analysts

    1 x Project manager

    1 x Back-end developer

    1 x Front-end developer

    2 x Odoo developers

    2 x QA engineers

    Challenge

    Our team aimed to solve the client’s outdated ERP issues like reporting problems, slow performance, and data silos with highly flexible and customizable software.

    Objectives

    Improve retail pipeline management

    Build smarter analytics and reporting

    Ensure advanced integration capabilities

    Solution & functionality

    We chose Odoo implementation to replace the client’s outdated ERP, leveraging its standard functions to meet 99% of their needs and adding custom features as required.

    Enterprise Resource Planning

    Our team’s Odoo ERP implementation automated critical business processes like inventory management, order processing, and financial reporting. We configured default features and added auxiliary functionality for online sales and POS terminals. Additionally, we implemented flexible pricing and compliant tax management and financial reporting modules.

    AI-powered Chatbot

    Using our AI expertise, we created an intelligent chatbot with advanced algorithms to automate rule-based tasks, reduce staff workload, and free up resources. Seamlessly integrated with the client’s website, resource planning, and customer management systems, our chatbot employs advanced AI to read user intentions and add human touch to automated customer support.

    Customer Relationship Management

    After the Odoo ERP implementation, we customized the CRM to integrate seamlessly and expand ERP capabilities. This centralized hub manages customer data, leads, and sales activities, automating processes like order generation and inventory updates. The CRM also streamlines customer management by centralizing contact details, purchase history, and communication logs for easy access and updates by sales reps.

    On top of that, we automated the e-commerce pipeline from lead capture to delivery. Pre-sale activities involve lead assignment and tracking, with additional features: 

    • Lead scoring
    • Automated emails
    • Reminders for managing quotes and feedback.

    Using Odoo-based CRM, sales reps easily handle customer support inquiries, service requests, and follow-ups to enhance customer loyalty.

    Paid Search Advertising & Branding

    We offered expert guidance on optimizing digital sales through Google Ads to drive increased visibility and targeted traffic. Our specialists also led a brand transformation, which resulted in heightened brand awareness and an influx of new customers to the client’s website.

    QR Codes

    As a tech-driven ERP Odoo implementation partner, Timspark improved inventory management using QR codes and enabled sales reps to track and label items accurately and streamline point-of-sale transactions. The unique QR codes printed on customer items facilitate quick and accurate identification, checkout, and access to discounts and promotions.

    Results and business value

    Timspark’s Odoo implementation liberates the client from outdated systems and fosters business growth. Our solution strategically enhances operational efficiency and profitability across all marketing activities.

    Benefits for client

    Timspark has successfully implemented a comprehensive Odoo system that replaces outdated ERP and boosts growth by integrating a custom CRM, QR codes for inventory, an AI chatbot, and optimized Google Ads. 

    38%

    more website visitors

    16%

    increase in online sales

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    Need assistance with a software project?

    Whether you're looking for expert developers or a full-service development solution, we're here to help. Get in touch!

      What happens next?

      An expert contacts you after thoroughly reviewing your requirements.

      If necessary, we provide you with a Non-Disclosure Agreement (NDA) and initiate the Discovery phase, ensuring maximum confidentiality and alignment on project objectives.

      We provide a project proposal, including estimates, scope analysis, CVs, and more.

      Meet our experts!

      Viktoryia Markevich

      Relationship manager

      Samuel Krendel

      Head of partnerships

      Call Center Monitoring Software That Automates 27% of Client Requests

      IoT PLATFORM

      Call Center Monitoring Software That Automates 27% of Client Requests

      Timspark crafted a tailored AI-powered call center monitoring software for a major telecom enterprise, seamlessly linking operators and customers within an integrated platform.

      #Telecom

      #AI

      #Python

      Client*

      The client operates as an internet provider and offers a diverse array of internet services to customers situated across the European Union.

      *We cannot provide any information about the client or specifics of the case study due to non-disclosure agreement (NDA) restrictions.

      Project in numbers

      duration

      13 months

      team

      20 specialists

      The team involved in the project

      industry

      Telecommunications

      solution

      AI call center software

      technologies

      React, Redux, Typescript, .Net Core, C#, .Net WebAPI, FluentMigrations, RabbitMQ, MassTransit, Windows, Linux, Python

      1 x Project manager

      2 x Business analysts

      2 x Front-end developers

      4 x Back-end developers

      3 x Full-stack developers

      1 x DevOps engineer

      1 x VoIP engineer

      2 x QA engineers

      1 x UI/UX designer

      1 x Solutions architect

      2 x ML engineers

      Challenge

      Our ISP client aimed to enhance customer satisfaction and support by developing custom call center software for improved scheduling. They required seamless integration with their CRM and task-tracking system to help operators quickly access client information and automate issue resolution.

      Major objective

      Empower customer service interactions with AI

      Related objectives

      Automate request processing

      Build intuitive interface

      Ensure security compliance

      Smoothly integrate infrastructure

      Solution & functionality

      Timspark created advanced AI-driven call center monitoring software to direct client calls to appropriate operators through AI-powered voice recognition and request identification. Our solution utilizes a .Net-based microservices architecture for robust back-end implementation, including SIP and soft PBX servers. 

      The front end, developed with React and Electron, offers a user-friendly desktop application interface. The system efficiently handles call routing, adhering to predefined regulations, and maintains GDPR compliance throughout its interconnected components to keep operator communication and responses swift.

      AI-driven voice recognition and call routing

      Our team integrated artificial intelligence into contact center operations to automate client support processes. Interactive voice response, call routing, and smart voice recognition capabilities are now managed by AI. Using modern natural language processing techniques and BERT models, the system engages callers, identifies their requests, and performs tasks like changing tariffs or ordering additional services. 

      For complex inquiries, the AI routes call to the appropriate operator or department to provide specialized assistance. Intelligent routing optimizes customer interactions and allows operators to focus on exceptional service delivery and the resolution of complex issues.

      Client request cards

      Our AI call center software automated card creation and enables operators to access and update client details quickly. When a call is received, the system identifies the client and presents their card with personal information and interaction history. Each card includes an action plan tailored to the request to guide operators through the resolution process with step-by-step instructions.

      Call recordings and statistics

      The call center monitoring software software securely stores call recordings and provides customizable statistics and tools for analytics. Supervisors can monitor performance metrics, track interactions processed by AI, and optimize team efficiency. This part of call center software features enhances issue resolution and facilitates call operator training through comprehensive call logging and recording.

      Automated task setting

      Integrated with the company’s task management and CRM systems, our call center monitoring software enables efficient task creation and assignment. Operators can generate tasks from client interactions, transferring all relevant details automatically. Task progress can be tracked within the system to provide supervisors with insights into workload distribution and resolution status.

      Results and business value

      Our AI call center software boosts task management, optimizes workloads, and streamlines customer support. Its user-friendly interface enables quick responses, while its flexibility promotes collaboration across departments beyond telecom services.

      Benefits for client

      Timspark’s AI call center software is a significant improvement that has reduced the workload for staff to keep focus on more complex customer issues.

      41%

      faster customer success

      27%

      of requests automated

      Related cases

      Need assistance with a software project?

      Whether you're looking for expert developers or a full-service development solution, we're here to help. Get in touch!

        What happens next?

        An expert contacts you after thoroughly reviewing your requirements.

        If necessary, we provide you with a Non-Disclosure Agreement (NDA) and initiate the Discovery phase, ensuring maximum confidentiality and alignment on project objectives.

        We provide a project proposal, including estimates, scope analysis, CVs, and more.

        Meet our experts!

        Viktoryia Markevich

        Relationship manager

        Samuel Krendel

        Head of partnerships

        How Computer Vision in Agriculture Helps Track Bee Population and Health

        Computer Vision in Agriculture

        How Computer Vision in Agriculture Helps Track Bee Population and Health

        Timspark used AI to make mobile computer vision software to track the beehive life. We also predict how the bee population will grow and how healthy it is overall.

        #AI

        #MobileDevelopment

        #ComputerVision

        Client*

        It was Timspark’s internal project. We were eager to independently grow expertise in Machine Learning and built an ML-powered app with prediction functionality for agriculture.

        Project in numbers

        duration

        6 months

        team

        4 specialists

        Team involved in the project

        industry

        Agriculture

        solution

        Mobile computer vision software for beehive tracking

        technologies

        Python, PyTorch, YOLOv3, Google Cloud Platform, DigitalOcean, Swift 5

        1 x Lead Data Scientist

        1 x iOS Developer

        1 x Data Engineer

        1 x Project Manager

        1 x QA

        Challenge

        Our team did it all for this project – from planning the product’s architecture to labeling the data and training the neural network. This hands-on approach to computer vision services helped us become experts in the field and led to a fully working product as the outcome. We tackled a set of machine learning challenges and industry-related standards of using computer vision in agriculture, too.

        Solution & functionality

        Our ready-made solution is a mobile app that uses computer vision in agriculture to count bees in the hive accurately. It also creates user-friendly charts and graphs, making it easy to monitor the hive’s growth and health.

        Object detection for beehive population count and health tracking

        We have harnessed object recognition technology, so now it is possible to scan and instantly figure out how many bees are in the hive. Also, the solution helps distinguish the regular bees from the queen bees.

        A modern user-friendly mobile app

        Our team built mobile computer vision software from the ground up with an easy-to-use interface. We also added a feature where a client can get automatic reports about the hive’s status using the information uploaded.

        Results and business value

        We’ve successfully crafted computer vision solutions for iOS, designed to assist beekeepers in caring for their beehives more effectively.

        Benefits 

        Our app offers a major time-saving advantage. With traditional manual inspections taking up to an hour per beehive, our computer vision services help beekeepers inspect a hive in just 10 minutes or even less.

        Related cases

        Need assistance with a software project?

        Whether you're looking for expert developers or a full-service development solution, we're here to help. Get in touch!

          What happens next?

          An expert contacts you after thoroughly reviewing your requirements.

          If necessary, we provide you with a Non-Disclosure Agreement (NDA) and initiate the Discovery phase, ensuring maximum confidentiality and alignment on project objectives.

          We provide a project proposal, including estimates, scope analysis, CVs, and more.

          Meet our experts!

          Viktoryia Markevich

          Relationship manager

          Samuel Krendel

          Head of partnerships

          AI-based Web Solution: X2 Sales Rise for Custom Sports Clubs

          AI-based Web Solution for Maximizing Sales

          AI-based Web Solution: X2 Sales Rise for Custom Sports Clubs

          The team developed an AI-based solution to automate the analysis of golf players’ positions and strokes, to boost sales for custom golf clubs manufacturing business.

          #AI

          #WebDevelopment

          #ComputerVision

          Client*

          The client is a major manufacturer of custom golf clubs.

          *We cannot provide any information about the client or specifics of the case study due to non-disclosure agreement (NDA) restrictions.

          Project in numbers

          duration

          3 months

          team

          6 specialists

          Team involved in the project

          industry

          Sport and Entertainment

          solution

          AI-powered analyzer for golf players

          technologies

          TensorFlow, Keras, Python, OpenCV, Mediapipe, LabelMe, MLFlow, NumPy, Colab, Matplotlib

          1 x Lead Data Scientist

          2 x Data Scientists

          1 x Data Engineer

          1 x Project Manager

          1 x QA

          Challenge

          Develop an AI-based product for analyzing golf players’ positions and strokes in order to design individually fitting golf clubs. The client was already using computer analysis software for analyzing the players’ movements and consistency of strokes and wanted to fully automate the process.

          Solution & functionality

          The team created an AI-powered solution capable of recognizing the golf club in a player’s hand and correctly estimating the angles of his joints (the posture).

          Detection of player’s positions and golf club

          Our team developed a model that successfully identifies the position of a person’s body, including their arms and legs, as well as the position of the golf club, using computer vision technology.

          Robust pose estimation

          Our developers enhanced the model to gather additional information by measuring the angles of specified body joints through computer vision technology. Data is captured either via a mobile device camera or via a pre-installed kiosk with a camera.

          Collection, analysis and processing of advanced metrics

          Timspark’s specialists developed and fine-tuned the classifier model to meet the project’s unique requirements. The model analyzes received images, determines the average class among all attributes of captured objects, and subsequently identifies the target audience for the advertisement.

          Results and business value

          The product was developed as an MVP. All the intended functionality operates with the help of computer vision and artificial intelligence technologies.

          Benefits for client

          The client remained highly content with the quality and speed of the team’s work. By successfully implementing the technology into their sales process, the client doubled their sales.

          Related cases

          Need assistance with a software project?

          Whether you're looking for expert developers or a full-service development solution, we're here to help. Get in touch!

            What happens next?

            An expert contacts you after thoroughly reviewing your requirements.

            If necessary, we provide you with a Non-Disclosure Agreement (NDA) and initiate the Discovery phase, ensuring maximum confidentiality and alignment on project objectives.

            We provide a project proposal, including estimates, scope analysis, CVs, and more.

            Meet our experts!

            Viktoryia Markevich

            Relationship manager

            Samuel Krendel

            Head of partnerships

            Let’s build something great together

              Let’s build something great together

                Let’s build something great together

                  Let’s build something great together

                    Let’s build something great together

                      Let’s build something great together