March 2, 2024

Increasing Automation To Propel Growth Of The Smart Pallet Sensors Market

The Global Smart Pallet Sensors Market is estimated to be valued at US$ 20.29 Bn in 2023 and is expected to exhibit a CAGR of 4.1% over the forecast period 2023-2030, as highlighted in a new report published by Coherent Market Insights.

Market Overview:
Smart pallet sensors help enable end-to-end supply chain visibility through real-time asset tracking and monitoring. These sensors detect factors like motion, temperature, humidity and other critical data regarding the pallets and products they carry during transit. This helps in monitoring environmental factors to prevent product damage and loss, provide proof of delivery, simplify order picking and improve warehouse operations through automation. They use technologies like RFID, GPS and cellular IoT for communication. Their small, affordable and rechargeable nature allows large scale deployment across the supply chain.

Market key trends:
One of the major trends in the market is the growing adoption of Industrial IoT technologies. With connectivity and real-time analytics, smart pallet sensors help enable predictive maintenance of equipment, enhanced operational efficiency and assist in decision making. They facilitate data driven insights for improvements across warehousing, transportation and manufacturing. Moreover, the increasing focus on supply chain visibility and automation is also driving their demand. Sensors help track assets, automate tasks like sortation and provide alerts in case of anomalies. This boosts productivity while minimizing human errors and costs. Advancements in miniaturization, long battery life and low power wide area network technologies will further support the large scale implementation of smart pallet sensors.

Porter’s Analysis
Threat of new entrants:
The threat of new entrants in the smart pallet sensors market is low as a result of presence of significant capital requirements and need for specialized machinery required to manufacture advanced smart pallet sensors along with well established players in the market.
Bargaining power of buyers: The bargaining power of buyers is moderate due to availability of various smart pallet sensors manufacturers. However, customized requirements from end-users increases their bargaining power.
Bargaining power of suppliers: The bargaining power of suppliers is moderate owing to availability of substitute components. However, integration of various components increases supplier power.
Threat of new substitutes: Threat of substitution is moderate as the availability of other emerging technologies could potentially replace smart pallet sensors. However, advantages of smart pallet sensors over traditional counterparts reduce the threat.
Competitive rivalry: High owing to presence of numerous global and domestic players offering similar products. Players differentiate their offerings through innovations.

Key Takeaways

The Global Smart Pallet Sensors Market Trend is expected to witness high growth, exhibiting CAGR of 4.1% over the forecast period, due to increasing need for predictive maintenance and real-time tracking in many industries.

Regional analysis: North America dominates the smart pallet sensors market and is expected to continue its dominance over the forecast period. This is attributed to presence of major players and developed automation industry in the region. Asia Pacific is expected to exhibit the fastest growth owing to increasing industrialization and manufacturing activities in countries such as China and India.

Key players: Key players operating in the smart pallet sensors market are ADLINK Technology Inc., Ahrma Group, Ambrosus, Chainvu, Ennomotive, Lightning Technologies LLC., LogTrade, Metiora, NFC Group, RM2., TronicsZone, and others. ADLINK Technology Inc. specializes in manufacturing industrial IoT platforms for sensing, computing and networking. Ambrosus develops blockchain-powered sensors for supply chain and logistics.

1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it