IoT is making buildings greener and more intelligent. Value versus affordability

IoT is making buildings greener and more intelligent. Value versus affordability

At a basic level a building — whether it was a primitive shelter or a modern steel and glass structure – is expected to provide a comfortable space for its occupants inside. The Internet of Things (IoT) transforms buildings from just being a ‘container’ for its occupants to being more cognitive and thus helping the occupants be more productive while minimizing the operational cost as well as environmental impact.
Making a smart building requires intelligent lighting, HVAC, fire alarms, building security and even elevator systems that are aware of each other and share intelligence so that the buildings can quickly adapt and respond based on needs of both occupants and the grid.

Even though operational costs for a smart home or smart building may be low, and home and building owners can save long-term energy and costs; but the short term still requires investment in deploying intelligence systems with sensor networks, gateways and cloud computation capabilities. A video doorbell is easily 10 times more expensive than a traditional doorbell; the same holds true for smart thermostats. So why are we as customers willing to pay the premium? It’s kind of all the more important to understand this from home automation point of view as the decision to make a home smarter or not is voluntary, but increasingly more of us are choosing this option.

One reason technology is making IoT more practical and affordable is the combination of smart sensing across multiple physical parameters and connectivity within a smart thermostat and video doorbell as well as the availability of smartphones that enables consumers to not only be surrounded by smart sensors and controls in their homes like an elock and video doorbell, but also let them manage those smart objects more effectively than ever before. The second reason is familiarity. Most consumers find it rather challenging to program a schedule on their sprinkler system. Because smartphones have become so ingrained in our lives, a smartphone application controlling our sprinkler system is often easier to interact with than a decades-old, product-specific human machine interface. The third reason is convenience: consumers can control their home even when they’re not inside – opening the garage door remotely or sending the secure authentication of a smart lock via an app. Some upfront costs on DIY home automation kits can help homeowners save on recurring third-party monitoring charges by providing sensors for water-leak detectors, door and window sensors, and video cameras for self-monitoring.

When it comes to commercial smart buildings, a key design consideration is often energy-efficiency and regulations like the California Energy Commission’s Title 24. Today, commercial buildings represent 40 percent of all U.S. energy consumption. A significant portion of that percentage is spent on heating, ventilation and air conditioning (HVAC). Having demand-controlled ventilation based on people counting can result in 15-20% savings compared to a fixed HVAC schedule. Adjusting the indoor light of a building based on the occupancy as well as the outside light coming in (a daylight harvester) can also help reduce the energy footprint of a building significantly.

Imagine using Bluetooth® low energy beacons to navigate through a complex maze of office spaces to find a conference room and not waste significant time just been lost or in a similar analogy not wasting time waiting for an elavator, rather elevator is there when you need it and is also pre-programmed to the floor you are headed, Imagine smart sensors can detect HVAC and elevator performance and accurately gauge predictive maintenance thus minimizing any downtime. These all lead to increased productivity of its occupants as a building is constantly processing and adapting.

A network of smart connected sensor nodes increasingly require to be run on batteries, and thus require a long battery life in order to avoid frequent battery replacement and incur maintainence costs. To address this challenge, any solutions will have to include a holistic system approach to implement, with low-power analog or nanopower analog for sensor processing; low-power management with extremely low Iq; and connectivity solutions that can quickly wake up, perform complex calculations like fast Fourier transform and then go back to sleep.

At CES this week, we see many technologies from TI and others that demonstrate how far we’ve come to building a smarter home or building. Some of demos include:
• IoT gateway demonstration: Includes multiple sensor nodes like carbon monoxide detector, occupancy detection, Temp Humidity sensor node that are shown with 10 years battery life on a coin cell as well as an e-lock that shows 5 years battery life with four AAs.
• Dual-band Sub-1 GHz and Bluetooth® low energy Sensor to Cloud with IoT gateway: Experience how to connect one, two or up to 50 sensors to the cloud over a long-range Sub-1 GHz wireless network, suitable for industrial and consumer applications such as building control and asset tracking. The demo and associated Sub-1 GHz Sensor to Cloud Industrial IoT Gateway Reference Design is powered by a TI Sitara™ AM335x processor and SimpleLink™ Sub-1 GHz CC1310 and dual-band CC1350 wireless microcontrollers (MCUs).
• Ready for Bluetooth 5? Get a sneak peek into the Bluetooth 5 standard with a demo showcasing 2Mbps mode which enables two times the speed of Bluetooth 4.2, faster over-the-air updates and increased responsiveness with TI’s SimpleLink™ Bluetooth low energy wireless MCU for IoT applications such as medical, health & fitness, wearables, remote controls, building automation and automotive (body control and lighting, infotainment).
• Keep up with other demonstrations and technologies from TI at CES.


 

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It Takes More Than Math to Design a Distribution Network

Distribution networks are the conduits that connect companies with their customers, so it is hardly surprising that the way these networks are designed has a critical impact on cost and customer service.

Companies commonly use mathematical optimization models to arrive at the best network design, but this approach is flawed in one key respect — it does not take into account changing market conditions during the several years it can take to complete a design project. This is particularly onerous in developing economies where markets tend to be extremely changeable.

Research carried out at the Malaysia Institute for Supply Chain Innovation (MISI) shows that supplementing mathematical models with analyses of external variables enables companies to develop the most efficient distribution networks. The research work was completed in collaboration with a leading Asian chemical manufacturer as part of a thesis project for the MIT-Malaysia Master of Science in Supply Chain Management.

Outdated models

Distribution network designs specify the locations of warehouses and how much product is allocated to each facility. A chemical company typically manufactures product in large plants to lower production costs by exploiting economies of scale. Product is shipped to numerous customer locations. The design of its distribution network, therefore, determines the total cost of delivering products to meet customer demand while maintaining the appropriate service levels.

There are many ways to configure a network to meet these goals. For example, a company can reduce its inventory holding cost by risk-pooling the inventory in a few warehouses. However, this option incurs higher transportation costs and longer lead times. Alternatively, a company could become extremely responsive to demand by stocking inventory in many warehouses. But such a strategy requires higher inventory volumes and hence higher carrying costs.

Mathematical models can be used to find the optimal solution, but this might not reflect real-world demands. External factors such as regional product demand, commercial real estate prices, and transportation costs can change markedly over the three- to five-year planning horizon that is common for these design projects.

Four-Stage Approach

The MISI research project tackled this problem in four steps.

First, an optimization model was designed to minimize total costs including the costs associated with transporting product, opening and closing warehouses in different locations, fixed warehouse operations, and maintaining inventory. The key consideration was deciding how many warehouses the company should support, and which time periods the facilities should operate within. The model also complied with various constraints such as the need to meet minimum safety stock levels.

Second, the researchers developed an exhaustive list of uncertainties that have a critical impact on the efficiency of distribution networks. Four business and macroeconomic factors were particularly relevant for the manufacturer’s operations: demand growth, oil price fluctuations, shifts in industrial real estate prices, and interest rate changes.

Third, we calculated a plausible range of values for each of these four macroeconomic factors over the planning horizon. The ranges were derived from an extensive search of industry forecasts and reports as well as expert opinion. Using these values, we ran the optimization model to create multiple scenarios based on market conditions driven by the macroeconomic factors. And we identified the optimal network design for each scenario using the mathematical optimization model. For each network design, the cost difference between each given scenario and its optimal version was calculated (known as the “regret”).

Finally, a comparison of the optimal designs — which specify which distribution centers should be operated in each period over the planning horizon — for the different scenarios suggested that one variable had the most impact on performance: the price of oil. A more detailed analysis of oil price effects was carried out.

When deciding which network design to adopt, the chemical company should look at the ones that minimize the regret for the different future scenarios.

Real-World Insights

This approach helps companies to design distribution networks that are aligned with real-world market conditions in two important ways:

  • It enhances quantitative mathematical models by considering a broad range of qualitative variables, employing techniques borrowed from scenario planning. The methodology provides a clearer picture of how a distribution network design might perform. Companies can focus on the key major environmental factors affecting the robustness of a network configuration, under various quantitative scenarios.
  • By using this approach, it is also possible to get a sense of which distribution scenarios are the most relevant, given the market changes that affect the way a network performs. It is possible to represent which of the scenarios considered are most likely to occur — a valuable insight for managers who are striving to develop the most efficient channels for distributing product to customers.


MIT Sloan Management Review

ZoneKey and Intel Unveil Broadcast Solution for Smart Classrooms, Retail and More

A recent conference in China confirmed that a quiet revolution in digital signage is on.

The moment is ripe for transformation. Costs for sensors, bandwidth and compute have decreased significantly, while cloud, streaming media, remote management and increasing performance are bringing new capabilities to business, retail, industry and education.

Attendees to the recent 71st Education Equipment Industry Conference in Nanning, Guangxi, China, discovered an Internet of Things (IoT) capable of transforming education. Industry leaders, solution providers and educators gathered to take smart digital classrooms to the next level. Interactivity, autonomous learning, universal access to education resources and digital literacy were priorities, as China looks to improve its education models in light of innovative technologies.

A personal highlight — coming from my focus on advanced digital signage technologies used across industries such as retail, education, healthcare and smart cities — was the announcement of the Intel Visual Data Reference Design Specification. This new reference design brings cloud capabilities to the edge of the network. It combines compute, network, storage, accelerators and platform control to enable new digital signage solutions. It is exciting to see the most forward-looking of solutions — one that enables integration of high-performance, high-quality streaming audio/video with big data analytics and edge intelligence — poised to transform the lives of students and educators (with similar promise for retail and industry). The Intel reference design has already been adopted by ZoneKey for its video record broadcasting application based on Uzel.

A man talks into a microphone.

And from my perspective, these innovations are sure to impact more than education. It’s easy to see the implications for retail and other industries using digital signage to rethink business models. Solution providers, OEMs and ODMs take note: streaming, interactive, data-informed video and audio with the performance and intelligence to operate from the edge to cloud will be a digital signage game changer.

More immersive experiences, high-performance video and audio, data-driven insight and seamless interactivity. It’s time to bring a new era of digital signage to market.

 

Digital Signage Goes to School

A slideshow presentation.

Enriching and expanding the learning experience is at the heart of new education applications based on the Intel Visual Data Reference Design Specification. Solutions, such as the ZoneKey video record broadcasting application, can bring more content into more classrooms, integrate record broadcasting systems and interactive whiteboards, and enable near-real-time responses based on big data analytics. By supporting both online and offline education and the cloud, digital signage solutions can provide massive media and education content resources to classrooms — whether urban or rural.

Students can engage in an active, collaborative learning process and benefit from remote learning. Schools and teachers can take advantage of content distribution features to release curricula, notifications, security notices and news.

 

What Can You Build?

People check out a slide show.

The ZoneKey application unveiled in China is a great example of turning R&D into opportunity for our next generation of learners. I encourage you to explore the Intel Visual Data Reference Design Specification and seize the opportunity for a wide range of education, business and industry solutions.

Usage models for the Intel Visual Data Reference Design Specification include:

  • Video-based products used for audio/video streaming, video analytics, teaching, presentations, student engagement and education-based VR applications
  • Audio/video processing and recording visual retail products used for digital signage, video walls, kiosks, video control rooms and interactive whiteboards
  • Content processing and analytic products used for data aggregation at the edge
  • Consolidation of back-end and cloud workloads
  • Creation of service enabler platform for Digital Signage as a Service (DSaaS) and Education as a Service (EaaS) solutions

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