1. A laser marking composition comprising
(I) a marking component comprising (a) at least one metal oxide is selected from bismuth vanadate, vanadium pentoxide, copper oxide, cobalt oxide, chromium oxide, iron oxide, zirconium oxide, red iron oxide, tungsten oxide, silica or tin oxide and (b) at least one oxidizingreducing agent selected from potassium permanganate, zinc phosphate, molybdenum oxide, sodium permanganate, calcium permanganate, ammonium permanganate, sodium perborate, silver oxide, osmium tetroxide, chromium trioxide, pyridinium chlorochromate, copper phosphate, ammonium phosphate or tricalcium phosphate; and, optionally,
(II) a binder,
wherein upon irradiation in a wavelength range of between about 700 nm and 14000 nm the laser marking composition bonds to a substrate to which it is contacted.
2. The composition of claim 1 wherein the metal oxide is selected from the group consisting of bismuth vanadate, cobalt oxide, vanadium pentoxide, copper oxide, chromium oxide, zirconium oxide and any combination thereof.
3. The composition of claim 1 wherein the binder comprises:
i) a resin selected from the group consisting of acrylics, acrylates, alkyds, cellulose, cellulose derivatives, polysaccharides, polysaccharide derivatives, rubber resins, ketones, maleics, formaldehydes, phenolics, epoxides, fumarics, hydrocarbons, isocyanate free polyurethanes, polyvinyl butyral, polyamides, shellac, polyvinyl alcohol and any combination thereof; and
ii) a solvent selected from the group consisting of methylated spirits, alkyl acetate, propanol, isopropanol, n-propyl acetate, toluene, xylene, cyclohexanone, alkoxyethanol, butoxyethanol, aromatic distillates having a boiling point of from about 200\xb0 C. to 310\xb0 C., water, and any combination thereof.
4. The composition of claim 1 further comprising one or more additives selected from the group consisting of plasticizers, wax, drying additives, chelating agents, antioxidants, anionic surfactants, zwitterionic surfactants, amphoteric surfactants, nonionic surfactants, defoamers, alkali additives, reducing agents, lubricating agents, pigments, sensitizers, alumina, titanium oxide, zinc oxide, kaolin, mica and any combination thereof.
5. The composition of claim 1 wherein irradiation is performed a range of between about 700 nm and 11000 nm.
6. The composition of claim 1 further comprising a pigment composition selected from monoazo pigments, C.I. Pigment Brown, C.I. Pigment Orange, C.I. Pigment Red, C.I. Pigment yellow; diazo pigments, C.I. Pigment Orange, anthanthrone pigments, anthraquinone pigments, C.I. Pigment Violet, anthrapyrimidine pigments, quinophthalone pigments, dioxazine pigments, flavanthrone pigments, C.I. Pigment Blue, isoindoline pigments, isoviolanthrone pigments, metal-complex pigments, C.I. Pigment Green; perinone pigments, perylene pigments, C.I. Pigment Black, phthalocyanine pigments, pyranthrone pigments, thioindigo pigments, triarylcarbonium pigments, Aniline Black, Aldazine Yellow, C.I. Pigment Brown, liquid crystal polymer pigments (LCP pigments) or any combination thereof.
7. The composition of claim 1 wherein the substrate comprises metal, ceramic, glass, porcelain, marble, natural stone, plastic, paper, rubber, wood, cardboard or a combination thereof.
8. The composition of claim 1 wherein the substrate is selected from the group consisting of glass, lead-free glass, ceramic tiles, sanitary ware, stoneware, porcelain, bricks, electronic quality ceramic substrates, marble, granite, slate, limestone, metal, steel, brass, copper, aluminum, tin, zinc, PVC, polyamides, polyolefins, polyethylenes, polycarbonates and polytetrafluoroethylene.
9. The composition of claim 1 wherein the oxidizingreducing agent selected from potassium permanganate, zinc phosphate, molybdenum oxide or sodium permanganate.
10. A method of laser marking a substrate in a desired pattern comprising:
a) obtaining a laser ink formulation comprising the composition of claim 1;
b) contacting the formulation with a substrate; and
c) irradiating the formulation with a laser having a wavelength of between about 700 nm and 11000 nm, thereby causing the composition to form a semi-permanent bond to the substrate and forming the desired pattern.
11. The method of claim 10 further comprising the step of determining a desired pattern to be formed on the substrate.
12. The method of claim 10 wherein the step of contacting the composition with a substrate comprises electrostatially applying a layer of the composition onto the substrate.
13. The method of claim 10 wherein the step of contacting the composition with a substrate comprises spraying a layer of the composition onto the substrate.
14. The method of claim 10 wherein the pattern is selected from the group consisting of a pattern, a bar code, an identifying code and a name.
15. The method according to claim 10, wherein the laser is selected from a fibre, diode, diode array or CO2 laser.
16. The method of claim 10 wherein the oxidizingreducing agent selected from potassium permanganate, zinc phosphate, molybdenum oxide or sodium permanganate.
17. The method of claim 10 wherein the substrate comprises metal, ceramic, glass, porcelain, marble, natural stone, plastic, paper, rubber, wood, cardboard, lead-free glass, ceramic tiles, sanitary ware, stoneware, bricks, electronic quality ceramic substrates, granite, slate, limestone, steel, brass, copper, aluminum, tin, zinc, PVC, polyamides, polyolefins, polyethylenes, polycarbonates, polytetrafluoroethylene or any combination thereof.
18. The method of claim 10 wherein the composition further comprises a pigment composition selected from monoazo pigments, C.I. Pigment Brown, C.I. Pigment Orange, C.I. Pigment Red, C.I. Pigment yellow; diazo pigments, C.I. Pigment Orange, anthanthrone pigments, anthraquinone pigments, C.I. Pigment Violet, anthrapyrimidine pigments, quinophthalone pigments, dioxazine pigments, flavanthrone pigments, C.I. Pigment Blue, isoindoline pigments, isoviolanthrone pigments, metal-complex pigments, C.I. Pigment Green; perinone pigments, perylene pigments, C.I. Pigment Black, phthalocyanine pigments, pyranthrone pigments, thioindigo pigments, triarylcarbonium pigments, Aniline Black, Aldazine Yellow, C.I. Pigment Brown, liquid crystal polymer pigments (LCP pigments) or any combination thereof.
19. A method for forming an image on a substrate, the method comprising the steps of:
spraying onto the substrate a composition according to claim 1, and
irradiating the substrate with a laser having a wavelength of between about 700 nm and 11000 nm.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method for indoor positioning, executed by a processing unit of a first reference node, comprising:
listening to a plurality of first broadcast signals of a plurality of second reference nodes;
obtaining a plurality of first signal measurements of the first broadcast signals;
obtaining identification information from a plurality of broadcast messages sent by the second reference nodes;
obtaining a first distance associated with each identification information; and
updating a first MLM (Machine Learning Model) according to the first signal measurements and the first distances,
wherein the first MLM describes a linear function between signal measurements and distances.
2. The method of claim 1, wherein the first signal measurement are RSSIs (Received Signal Strength Indications) or LQIs (Link Quality Indicators).
3. The method of claim 1, wherein the identification information is a device identification or a network address.
4. The method of claim 1, wherein the first distance associated with each identification information is obtained from a storage device.
5. The method of claim 1, further comprising:
determining whether each first signal measurement exceeds a first threshold value; and
when the first signal measurement exceeds the first threshold value, obtaining the corresponding identification information from the corresponding broadcast message sent by the corresponding second reference node.
6. The method of claim 5, further comprising:
collecting a plurality of second MLMs from the second reference nodes;
calculating an average MLM according to the second MLMs;
calculating the difference between the first MLM and the average MLM;
determining whether the difference exceeds a second threshold value; and
when the difference exceeds the second threshold value, overwriting the first MLM stored in a memory with the average MLM.
7. The method of claim 1, further comprising:
receiving a positioning request from a blind node;
calculating a second signal measurement of a second broadcast signal of the blind node;
converting the second signal measurement into a second distance according to the first MLM; and
replying with a three-dimensional location and the second distance of the first reference node to the blind node, thereby enabling the blind node to calculate a three-dimensional location of the blind node accordingly.
8. The method of claim 1, further comprising:
receiving an echo message from a blind node, which comprises identification information of the blind node;
calculating a second signal measurement of a reply signal of the blind node;
converting the second signal measurement into a second distance according to the first MLM; and
transmitting the identification information of the blind node, identification information and a three-dimensional location of the first reference node, and the second distance to a positioning node, thereby enabling the blind node to calculate a three-dimensional location of the blind node.
9. A method for indoor positioning, executed by a processing unit of a first reference node, comprising:
generating a first MLM (Machine Learning Model);
collecting a plurality of second MLMs from a plurality of second reference nodes;
calculating an average MLM according to the second MLMs;
calculating the difference between the first MLM and the average MLM;
determining whether the difference exceeds a threshold value; and
when the difference exceeds the threshold value, overwriting the first MLM stored in a memory with the average MLM,
wherein the average MLM describes a linear function between signal measurements and distances.
10. The method of claim 9, further comprising:
receiving a positioning request from a blind node;
calculating a signal measurement of a broadcast signal of the blind node;
converting the signal measurement into a distance according to the average MLM; and
replying with a three-dimensional location and the distance between the first reference node and the blind node, thereby enabling the blind node to calculate a three-dimensional location of the blind node accordingly.
11. The method of claim 9, further comprising:
receiving an echo message from a blind node, which comprises identification information of the blind node;
calculating a signal measurement of a reply signal of the blind node;
converting the signal measurement into a distance according to the average MLM; and
transmitting the identification information of the blind node, identification information and a three-dimensional location of the first reference node, and the distance to a positioning node, thereby enabling the blind node to calculate a three-dimensional location of the blind node.
12. A system for indoor positioning, comprising:
a communications interface; and
a processing unit, coupled to the communications interface, listening to a plurality of first broadcast signals of a plurality of second reference nodes via the communications interface; obtaining a plurality of first signal measurements of the first broadcast signals; obtaining identification information from a plurality of broadcast messages sent by the second reference nodes; obtaining a first distance associated with each identification information; and updating a first MLM (Machine Learning Model) according to the first signal measurements and the first distances, wherein the first MLM describes a linear function between signal measurements and distances.
13. The system of claim 12, wherein the first signal measurements are RSSIs (Received Signal Strength Indications) or LQIs (Link Quality Indicators).
14. The system of claim 12, wherein the identification information is a device identification or a network address.
15. The system of claim 12, further comprising:
a storage device,
wherein the first distance associated with each identification information is obtained from the storage device.
16. The system of claim 12, wherein the processing unit determines whether each first signal measurement exceeds a first threshold value; and when the first signal measurement exceeds the first threshold value, obtains the corresponding identification information from the corresponding broadcast message sent by the corresponding second reference node.
17. The system of claim 16, further comprising:
a memory, storing the first MLM,
wherein the processing unit collects a plurality of second MLMs from the second reference nodes; calculates an average MLM according to the second MLMs; calculates the difference between the first MLM and the average MLM; determines whether the difference exceeds a second threshold value; and when the difference exceeds the second threshold value, overwrites the first MLM stored in the memory with the average MLM.
18. The system of claim 12, wherein the processing unit receives a positioning request from a blind node; calculates a second signal measurement of a second broadcast signal of the blind node; converts the second signal measurement into a second distance according to the first MLM; and replies with a three-dimensional location and the second distance of the first reference node to the blind node, thereby enabling the blind node to calculate a three-dimensional location of the blind node accordingly.
19. The system of claim 12, wherein the processing unit receives an echo message from a blind node, which comprises identification information of the blind node; calculates a second signal measurement of a reply signal of the blind node; converts the second signal measurement into a second distance according to the first MLM; and transmits the identification information of the blind node, identification information and a three-dimensional location of the first reference node, and the second distance to a positioning node, thereby enabling the blind node to calculate a three-dimensional location of the blind node.
20. A system for indoor positioning, comprising:
a communications interface;
a memory; and
a processing unit, coupled to the communications interface and the memory, generating the first MLM; storing the first MLM in the memory; collecting a plurality of second MLMs from a plurality of second reference nodes via the communications interface; calculating an average MLM according to the second MLMs; calculating the difference between the first MLM and the average MLM; determining whether the difference exceeds a threshold value; and when the difference exceeds the threshold value, overwriting the first MLM stored in the memory with the average MLM, wherein the average MLM describes a linear function between signal measurements and distances.
21. The system of claim 20, wherein the processing unit receives a positioning request from a blind node via the communications interface; calculates a signal measurement of a broadcast signal of the blind node; converts the signal measurement into a distance according to the average MLM; and replies with a three-dimensional location and the distance of the first reference node to the blind node, thereby enabling the blind node to calculate a three-dimensional location of the blind node accordingly.
22. The system of claim 20, wherein the processing unit receives an echo message from a blind node, which comprises identification information of the blind node, via the communications interface; calculates a signal measurement of a reply signal of the blind node; converts the signal measurement into a distance according to the average MLM; and transmits the identification information of the blind node, identification information and a three-dimensional location of the first reference node, and the distance to a positioning node, thereby enabling the blind node to calculate a three-dimensional location of the blind node.