What is detection? Within the context of this report, detection is defined as systems solutions and applications whose purpose is to gather data that is of an unstructured nature. In other words, detection systems in this context are those systems and solutions facilitate aggregation of Big Data. Detection systems include sensors, presence and location systems. Sensors exist within consumer sector as well as industry. Presence falls within the realm of telecommunications and general ICT systems.
Presence is really not an application by itself but is rather an enabler of applications, adding value to them. We shall define presence information within a telecommunications context including the state of an object or device, status of attachment or engagement, device type, usage or activity, and coarse location information. All of these attributes can be used to distinguish the presence of an entity or object. In telecommunications or computing an object or device can be many things including a PC or laptop, circuit-switched or IP-based phone, mobile/cellular phone, or other wireless data, voice or signaling device.
Sensors in Industry
There are a variety of sensor types and applications within industry including:
*Industrial Scenarios: This area includes measurements of physical parameters such as temperature or vibration of manufacturing machinery/equipment, detecting toxic chemicals, fluid, gas pressure and other variations from the norm.
*Consumer Scenarios: Most of these involve safety and well-being such as accelerometers, gyroscope, temperature, flooding, smoke, carbon monoxide, glass breakage, and proximity (of various types).
*Business Scenarios: These are many and varied such as monitoring traffic, smart building (HVAC, lighting, security, etc.), and others.
*Environmental: This includes monitoring tsunami, seismic activity, fires and more.
Sensors in Retail Sector
Sensors in the consumer sector typically utilize some form of RFID. Some people know about this as NFC (near field communications). Even if they don’t know that term, they have probably used it whether paying for gas at the station or making a purchase at the supermarket. General RFID systems are used in the consumer sector in retail sales, for example as a means of tracking the location of clothing and preventing theft.
Despite having been around for more than a decade, only now is NFC beginning to make a serious assault on the marketing industry. Much of the focus on NFC over the last couple of years has been around contactless payment. There has been little if any discussion about capturing data from NFC transactions for analytics.
NFC technology works by sending data via radio waves between two devices that each has an NFC chip when the two come into close proximity, typically within a foot. It works by the same methodology as RFID (Radio Frequency Identification) tags. In one scenario, a customer picks up an RFID hanger holding a shirt and examines the garment while viewing relevant product knowledge displayed on a nearby panel. The customer enters a fitting space and tries on the garment. An RFID reader records this action. The customer then decides to shop for the blouse, leaves the fitting area (an action duly noted by the RFID reader), and completes the acquisition via NFC on her smartphone. As she completes her purchase, she posts a photo about her purchase on her Facebook wall.
This single transaction creates five different data records:
*Picking up the hanger
*Entering the fitting room
*Leaving the fitting room
*Purchasing the blouse
*Making the Facebook post
This represents a huge and fast growing opportunity for Big Data as a Service (BDaaS) providers to take advantage of data collection, analytics and generation of business intelligence information for retailers. However, this is just one example of data collection. As indicated in the above illustration, there are several places where the so-called “Big Data” (unstructured data) can be captured.
M2M, IoT, Sensors, and Connected World: Market and Forecast 2015 – 2020 assesses the overall sensor marketplace for IoT, evaluates leading vendors, identifies key IoT functionality in support of sensors, and forecasts the market for sensor adoption and revenue. The report covers three key areas within the sensor ecosystem:
*Sensors: H/W and S/W designed and Developed to Suit IoT deployments
*Protocols: Designed and developed to drive Wireless Sensor Network (WSN) in IoT
*Sensor Data: Through Sensor Fusion / Multi-sensing / Soft Sensors
Key findings from report include:
*EMEA will lead the market 13.5 billion sensors in 2020 with a CAGR of 51.3%
*North America ranks second with 9 billion units by 2020 with a CAGR of 46.6%
*A key ecosystem function, IoT Mediation will evolve in three stages as assessed in the report
*Most of sensors will be used in industrial applications followed by personal IoT, largely in the wearables category
*IIoT will comprise 94% of the total IIoT business through 2020, representing a huge driver for various sensor-enabled industrial apps